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@@ -1,9 +1,7 @@
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# LLM Prose Tells
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All of these show up in human writing occasionally, and no single one is
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conclusive on its own. The difference is concentration, because a person might
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lean on one or two of these habits across an entire essay while LLM output will
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use fifteen of them per paragraph, consistently, throughout the entire piece.
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A catalog of structural, lexical, and rhetorical patterns found in LLM-generated
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prose.
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---
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@@ -11,15 +9,16 @@ use fifteen of them per paragraph, consistently, throughout the entire piece.
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### The Em-Dash Pivot: "Not X—but Y"
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A negation followed by an em-dash and a reframe. The single most recognizable
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LLM construction.
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A negation followed by an em-dash and a reframe.
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> "It's not just a tool—it's a paradigm shift." "This isn't about
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> technology—it's about trust."
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Models produce this at roughly 10–50x the rate of human writers, and when it
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appears four times in the same essay you're almost certainly reading generated
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text.
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### Em-Dash Overuse Generally
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Even outside the "not X but Y" pivot, models substitute em-dashes for commas,
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semicolons, parentheses, colons, and periods. The em-dash can replace any other
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punctuation mark, and models default to it for that reason.
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### The Colon Elaboration
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@@ -27,85 +26,91 @@ A short declarative clause, then a colon, then a longer explanation.
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> "The answer is simple: we need to rethink our approach from the ground up."
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Models reach for this in nearly every other paragraph. The construction itself
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is perfectly normal, which is why the frequency is what gives it away.
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### The Triple Construction
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> "It's fast, it's scalable, and it's open source."
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Three parallel items in a list, usually escalating, with exactly three items
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every time (rarely two, almost never four) and strict grammatical parallelism
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that human writers rarely bother maintaining.
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Three parallel items in a list, usually escalating. Always exactly three (rarely
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two, never four) with strict grammatical parallelism.
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### The Staccato Burst
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> "This matters. It always has. And it always will." "The data is clear. The
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> trend is undeniable. The conclusion is obvious."
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Runs of very short sentences at the same cadence. Human writers will use a short
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sentence for emphasis occasionally, but they don't stack three or four of them
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in a row at matching length, because real prose has variable rhythm. When you
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see a paragraph where every sentence is under ten words and they're all roughly
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the same size, that mechanical regularity is a strong signal.
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Runs of very short sentences at the same cadence and matching length.
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### The Two-Clause Compound Sentence
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An independent clause, a comma, a conjunction ("and," "but," "which,"
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"because"), and a second independent clause of similar length. Every sentence
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becomes two balanced halves.
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> "The construction itself is perfectly normal, which is why the frequency is
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> what gives it away." "They contain zero information, and the actual point
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> always comes in the paragraph that follows them." "The qualifier never changes
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> the argument that follows it, and its purpose is to perform nuance rather than
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> to express an actual reservation."
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Human prose has sentences with one clause, sentences with three, sentences that
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start with a subordinate clause before reaching the main one, sentences that
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embed their complexity in the middle.
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### Uniform Sentences Per Paragraph
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Model-generated paragraphs almost always contain between three and five
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sentences, and this count holds remarkably steady across an entire piece. If the
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first paragraph has four sentences, nearly every subsequent paragraph will too.
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Human writers produce much more varied paragraph lengths — a single sentence
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followed by one that runs eight or nine — as a natural result of following the
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shape of an idea rather than filling a template.
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Model-generated paragraphs contain between three and five sentences, a count
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that holds steady across a piece. If the first paragraph has four sentences,
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every subsequent paragraph will too.
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### The Dramatic Fragment
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Sentence fragments used as standalone paragraphs for emphasis, like "Full stop."
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or "Let that sink in." on their own line. One of these in an entire essay is a
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stylistic choice. One per section is a tic, and models drop them in at that rate
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or higher.
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Sentence fragments used as standalone paragraphs for emphasis.
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> "Full stop." "Let that sink in."
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### The Pivot Paragraph
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> "But here's where it gets interesting." "Which raises an uncomfortable truth."
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One-sentence paragraphs that exist only to transition between ideas. They
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contain zero information, and the actual point always comes in the paragraph
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that follows them. Delete every one of these and the piece reads better.
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One-sentence paragraphs that exist only to transition between ideas, containing
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zero information. The actual point is always in the next paragraph.
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### The Parenthetical Qualifier
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> "This is, of course, a simplification." "There are, to be fair, exceptions."
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Parenthetical asides inserted to look thoughtful. The qualifier almost never
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changes the argument that follows it, and its purpose is to perform nuance
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rather than to express an actual reservation about what's being said.
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Parenthetical asides inserted to perform nuance without ever changing the
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argument.
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### The Unnecessary Contrast
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Models append a contrasting clause to statements that don't need one, tacking on
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"whereas," "as opposed to," "unlike," or "except that" to draw a comparison that
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adds nothing the reader couldn't already infer.
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A contrasting clause appended to a statement that doesn't need one, using
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"whereas," "as opposed to," "unlike," or "except that."
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> "Models write one register above where a human would, whereas human writers
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> tend to match register to context." "The lists use rigidly parallel grammar,
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> as opposed to the looser structure you'd see in human writing."
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> tend to match register to context."
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The first clause already makes the point. The contrasting clause just restates
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it from the other direction. This happens because models are trained to be
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thorough and to anticipate objections, so they compulsively spell out both sides
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of a distinction even when one side is obvious. If you delete the "whereas"
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clause and the sentence still says everything it needs to, the contrast was
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filler.
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The contrasting clause restates what the first clause already said. If you
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delete the "whereas" clause and the sentence still says everything it needs to,
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the contrast was filler.
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### Unnecessary Elaboration
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Models keep going after the sentence has already made its point.
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> "A person might lean on one or two of these habits across an entire essay, but
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> LLM output will use fifteen of them per paragraph, consistently, throughout
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> the entire piece."
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This sentence could end at "paragraph." The words after it repeat what "per
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paragraph" already means. If you can cut the last third of a sentence without
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losing meaning, the last third shouldn't be there.
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### The Question-Then-Answer
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> "So what does this mean for the average user? It means everything."
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A rhetorical question immediately followed by its own answer. Models lean on
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this two or three times per piece because it generates the feeling of forward
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momentum without requiring any actual argumentative work. A human writer might
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do it once.
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A rhetorical question immediately followed by its own answer.
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---
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@@ -113,39 +118,38 @@ do it once.
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### Overused Intensifiers
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The following words appear at dramatically elevated rates in model output
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compared to human-written text: "crucial," "vital," "robust," "comprehensive,"
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"fundamental," "arguably," "straightforward," "noteworthy," "realm,"
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"landscape," "leverage" (used as a verb), "delve," "tapestry," "multifaceted,"
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"nuanced" (which models almost always apply to their own analysis), "pivotal,"
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"unprecedented" (frequently applied to things that have plenty of precedent),
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"navigate," "foster," "underscores," "resonates," "embark," "streamline," and
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"spearhead." Three or more on the same page is a strong signal.
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"Crucial," "vital," "robust," "comprehensive," "fundamental," "arguably,"
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"straightforward," "noteworthy," "realm," "landscape," "leverage" (as a verb),
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"delve," "tapestry," "multifaceted," "nuanced" (applied to the model's own
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analysis), "pivotal," "unprecedented" (applied to things with plenty of
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precedent), "navigate," "foster," "underscores," "resonates," "embark,"
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"streamline," "spearhead."
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### Elevated Register Drift
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Models consistently write one register above where a human would for the same
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content, replacing "use" with "utilize," "start" with "commence," "help" with
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"facilitate," "show" with "demonstrate," "try" with "endeavor," "change" with
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"transform," and "make" with "craft." The tendency holds across every topic
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regardless of audience.
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Models write one register above where a human would. "Use" becomes "utilize."
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"Start" becomes "commence." "Help" becomes "facilitate." "Show" becomes
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"demonstrate." "Try" becomes "endeavor." "Change" becomes "transform." "Make"
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becomes "craft."
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### Filler Adverbs
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"Importantly," "essentially," "fundamentally," "ultimately," "inherently,"
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"particularly," and "increasingly" get dropped in to signal that something
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matters. If the writing itself has already made the importance clear through its
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content and structure, these adverbs aren't doing anything except taking up
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space.
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"particularly," "increasingly." Dropped in to signal that something matters when
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the writing itself should make the importance clear.
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### The "Almost" Hedge
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Instead of saying a pattern "always" or "never" does something, models write
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"almost always," "almost never," "almost certainly," "almost exclusively." A
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micro-hedge, less obvious than the full hedge stack.
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### "In an era of..."
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> "In an era of rapid technological change..."
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Almost exclusively a model habit as an essay opener. The model uses it to stall
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while it figures out what the actual argument is, because almost no human writer
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begins a piece by zooming out to the civilizational scale before they've said
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anything specific.
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Used to open an essay. The model is stalling while it figures out what the
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actual argument is.
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---
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@@ -156,25 +160,20 @@ anything specific.
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> "While X has its drawbacks, it also offers significant benefits."
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Every argument followed by a concession, every criticism softened. A direct
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artifact of RLHF training, which penalizes strong stances and produces models
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that reflexively both-sides everything even when a clear position would serve
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the reader better.
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artifact of RLHF training, which penalizes strong stances.
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### The Throat-Clearing Opener
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> "In today's rapidly evolving digital landscape, the question of data privacy
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> has never been more important."
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The first paragraph of most model-generated essays adds no information. You can
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delete it and the piece improves immediately, because the actual argument always
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starts in the second paragraph.
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The first paragraph adds no information. Delete it and the piece improves.
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### The False Conclusion
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> "At the end of the day, what matters most is..." "Moving forward, we must..."
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The high school "In conclusion,..." dressed up for a professional audience. It
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signals that the model is wrapping up without actually landing on anything.
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The high school "In conclusion,..." dressed up for a professional audience.
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### The Sycophantic Frame
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@@ -185,9 +184,9 @@ No one who writes for a living opens by complimenting the assignment.
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### The Listicle Instinct
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Models default to numbered or bulleted lists even when prose would be more
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appropriate. The lists almost always contain exactly 3, 5, 7, or 10 items (never
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4, 6, or 9), use rigidly parallel grammar, and get introduced with a preamble
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like "Here are the key considerations:"
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appropriate. The lists contain exactly 3, 5, 7, or 10 items (never 4, 6, or 9),
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use rigidly parallel grammar, and get introduced with a preamble like "Here are
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the key considerations:"
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### The Hedge Stack
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@@ -195,15 +194,13 @@ like "Here are the key considerations:"
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> cases it can potentially offer significant benefits."
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Five hedges in one sentence ("worth noting," "while," "may not be," "in many
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cases," "can potentially"), communicating almost nothing, because the model
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would rather be vague than risk being wrong about anything.
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cases," "can potentially"), communicating nothing.
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### The Empathy Performance
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> "This can be a deeply challenging experience." "Your feelings are valid."
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Generic emotional language that could apply equally to a bad day at work or a
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natural disaster. That interchangeability is exactly what makes it identifiable.
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Generic emotional language that could apply to anything.
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---
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@@ -211,23 +208,20 @@ natural disaster. That interchangeability is exactly what makes it identifiable.
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### Symmetrical Section Length
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If the first section of a model-generated essay runs about 150 words, every
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subsequent section will fall between 130 and 170. Human writing is much more
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uneven, with some sections running 50 words and others running 400.
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If the first section runs about 150 words, every subsequent section will fall
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between 130 and 170.
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### The Five-Paragraph Prison
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Model essays follow a rigid introduction-body-conclusion arc even when nobody
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asked for one. The introduction previews the argument, the body presents 3–5
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supporting points, and the conclusion restates the thesis in slightly different
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words.
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asked for one. The introduction previews the argument, the body presents 3 to 5
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points, the conclusion restates the thesis.
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### Connector Addiction
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Look at the first word of each paragraph in model output and you'll find an
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unbroken chain of transition words — "However," "Furthermore," "Moreover,"
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"Additionally," "That said," "To that end," "With that in mind," "Building on
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this." Human prose moves between ideas without announcing every transition.
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The first word of each paragraph forms an unbroken chain of transition words:
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"However," "Furthermore," "Moreover," "Additionally," "That said," "To that
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end," "With that in mind," "Building on this."
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### Absence of Mess
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@@ -237,10 +231,6 @@ without explaining it, make a joke that risks falling flat, leave a thought
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genuinely unfinished, or keep a sentence the writer liked the sound of even
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though it doesn't quite work.
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Human writing does all of those things. The total absence of rough edges, false
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starts, and odd rhythmic choices is one of the strongest signals that text was
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machine-generated.
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---
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## Framing Tells
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@@ -249,45 +239,27 @@ machine-generated.
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> "This has implications far beyond just the tech industry."
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Zooming out to claim broader significance without substantiating it. The model
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has learned that essays are supposed to gesture at big ideas, so it gestures,
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but nothing concrete is behind the gesture.
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Zooming out to claim broader significance without substantiating it.
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### "It's important to note that..."
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This phrase and its variants ("it's worth noting," "it bears mentioning," "it
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should be noted") appear at absurd rates in model output and function as verbal
|
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tics before a qualification the model believes someone expects.
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should be noted") function as verbal tics before a qualification the model
|
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believes someone expects.
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### The Metaphor Crutch
|
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Models rely on a small, predictable set of metaphors — "double-edged sword,"
|
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"tip of the iceberg," "north star," "building blocks," "elephant in the room,"
|
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"perfect storm," "game-changer" — and reach for them with unusual regularity
|
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across every topic. The pool they draw from is noticeably smaller than what
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human writers use.
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---
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## How to Actually Spot It
|
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No single pattern on this list proves anything by itself, since humans use
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em-dashes and humans write "crucial" and humans ask rhetorical questions.
|
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What gives it away is how many of these show up at once. Model output will hit
|
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10–20 of these patterns per page, while human writing might trigger 2–3,
|
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distributed unevenly and mixed with idiosyncratic constructions that no model
|
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would produce. When every paragraph on the page reads like it came from the same
|
||||
careful, balanced, slightly formal, structurally predictable process, it was
|
||||
probably generated by one.
|
||||
Models rely on a small, predictable set of metaphors: "double-edged sword," "tip
|
||||
of the iceberg," "north star," "building blocks," "elephant in the room,"
|
||||
"perfect storm," "game-changer."
|
||||
|
||||
---
|
||||
|
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## Copyediting Checklist: Removing LLM Tells
|
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|
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Follow this checklist when editing any document to remove machine-generated
|
||||
patterns. Go through the entire list for every piece, and do at least two full
|
||||
passes, because fixing one pattern often introduces another.
|
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patterns. Do at least two full passes, because fixing one pattern often
|
||||
introduces another.
|
||||
|
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### Pass 1: Word-Level Cleanup
|
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|
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@@ -296,13 +268,12 @@ passes, because fixing one pattern often introduces another.
|
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"straightforward," "noteworthy," "realm," "landscape," "leverage," "delve,"
|
||||
"tapestry," "multifaceted," "nuanced," "pivotal," "unprecedented,"
|
||||
"navigate," "foster," "underscores," "resonates," "embark," "streamline,"
|
||||
"spearhead") and replace each one with a plainer word, or delete it entirely
|
||||
if the sentence works without it.
|
||||
"spearhead") and replace each one with a plainer word, or delete it if the
|
||||
sentence works without it.
|
||||
|
||||
2. Search for the filler adverbs ("importantly," "essentially," "fundamentally,"
|
||||
2. Search for filler adverbs ("importantly," "essentially," "fundamentally,"
|
||||
"ultimately," "inherently," "particularly," "increasingly") and delete every
|
||||
instance where the sentence still makes sense without it, which will be most
|
||||
of them.
|
||||
instance where the sentence still makes sense without it.
|
||||
|
||||
3. Look for elevated register drift ("utilize," "commence," "facilitate,"
|
||||
"demonstrate," "endeavor," "transform," "craft" and similar) and replace with
|
||||
@@ -310,87 +281,171 @@ passes, because fixing one pattern often introduces another.
|
||||
|
||||
4. Search for "it's important to note," "it's worth noting," "it bears
|
||||
mentioning," and "it should be noted" and delete the phrase in every case.
|
||||
The sentence that follows always stands on its own.
|
||||
|
||||
5. Search for the stock metaphors ("double-edged sword," "tip of the iceberg,"
|
||||
"north star," "building blocks," "elephant in the room," "perfect storm,"
|
||||
"game-changer," "at the end of the day") and replace them with something
|
||||
specific to the topic, or just state the point directly without a metaphor.
|
||||
specific to the topic, or just state the point directly.
|
||||
|
||||
6. Search for "almost" used as a hedge ("almost always," "almost never," "almost
|
||||
certainly," "almost exclusively") and decide in each case whether to commit
|
||||
to the unqualified claim or to drop the sentence entirely.
|
||||
|
||||
7. Search for em-dashes and replace each one with the punctuation mark that
|
||||
would normally be used in that position (comma, semicolon, colon, period, or
|
||||
parentheses). If you can't identify which one it should be, the sentence
|
||||
needs to be restructured.
|
||||
|
||||
8. Remove redundant adjectives. For each adjective, ask whether the sentence
|
||||
changes meaning without it. "A single paragraph" means the same as "a
|
||||
paragraph." "An entire essay" means the same as "an essay." If the adjective
|
||||
doesn't change the meaning, cut it.
|
||||
|
||||
9. Remove unnecessary trailing clauses. Read the end of each sentence and ask
|
||||
whether the last clause restates what the sentence already said. If so, end
|
||||
the sentence earlier.
|
||||
|
||||
### Pass 2: Sentence-Level Restructuring
|
||||
|
||||
6. Find every em-dash pivot ("not X—but Y," "not just X—Y," "more than X—Y") and
|
||||
rewrite it as two separate clauses or a single sentence that makes the point
|
||||
without the negation-then-correction structure.
|
||||
10. Find every em-dash pivot ("not X—but Y," "not just X—Y," "more than X—Y")
|
||||
and rewrite it as two separate clauses or a single sentence that makes the
|
||||
point without the negation-then-correction structure.
|
||||
|
||||
7. Find every colon elaboration and check whether it's doing real work. If the
|
||||
clause before the colon could be deleted without losing meaning, rewrite the
|
||||
sentence to start with the substance that comes after the colon.
|
||||
11. Find every colon elaboration and check whether it's doing real work. If the
|
||||
clause before the colon could be deleted without losing meaning, rewrite the
|
||||
sentence to start with the substance that comes after the colon.
|
||||
|
||||
8. Find every triple construction (three parallel items in a row) and either
|
||||
reduce it to two, expand it to four or more, or break the parallelism so the
|
||||
items don't share the same grammatical structure.
|
||||
12. Find every triple construction (three parallel items in a row) and either
|
||||
reduce it to two, expand it to four or more, or break the parallelism so the
|
||||
items don't share the same grammatical structure.
|
||||
|
||||
9. Find every staccato burst (three or more short sentences in a row at similar
|
||||
length) and combine at least two of them into a longer sentence, or vary
|
||||
their lengths so they don't land at the same cadence.
|
||||
13. Find every staccato burst (three or more short sentences in a row at similar
|
||||
length) and combine at least two of them into a longer sentence, or vary
|
||||
their lengths so they don't land at the same cadence.
|
||||
|
||||
10. Find every unnecessary contrast ("whereas," "as opposed to," "unlike," "as
|
||||
14. Find every unnecessary contrast ("whereas," "as opposed to," "unlike," "as
|
||||
compared to," "except that") and check whether the contrasting clause adds
|
||||
information that isn't already obvious from the main clause. If the sentence
|
||||
says the same thing twice from two directions, delete the contrast.
|
||||
information not already obvious from the main clause. If the sentence says
|
||||
the same thing twice from two directions, delete the contrast.
|
||||
|
||||
11. Find every rhetorical question that is immediately followed by its own
|
||||
15. Check for the two-clause compound sentence pattern. If most sentences in a
|
||||
passage follow the "\[clause\], \[conjunction\] \[clause\]" structure, first
|
||||
try removing the conjunction and second clause entirely, since it's often
|
||||
redundant. If the second clause does carry meaning, break it into its own
|
||||
sentence, start the sentence with a subordinate clause, or embed a relative
|
||||
clause in the middle instead of appending it at the end.
|
||||
|
||||
16. Find every rhetorical question that is immediately followed by its own
|
||||
answer and rewrite the passage as a direct statement.
|
||||
|
||||
12. Find every sentence fragment being used as its own paragraph and either
|
||||
delete it or expand it into a complete sentence that adds actual
|
||||
information.
|
||||
17. Find every sentence fragment being used as its own paragraph and either
|
||||
delete it or expand it into a complete sentence that adds information.
|
||||
|
||||
13. Find every pivot paragraph ("But here's where it gets interesting." and
|
||||
similar) and delete it. The paragraph after it always contains the actual
|
||||
point.
|
||||
18. Check for unnecessary elaboration. Read every clause, phrase, and adjective
|
||||
in each sentence and ask whether the sentence loses meaning without it. If
|
||||
you can cut it and the sentence still says the same thing, cut it.
|
||||
|
||||
19. Check each pair of adjacent sentences to see if they can be merged into one
|
||||
sentence cleanly. If a sentence just continues the thought of the previous
|
||||
one, combine them using a participle, a relative clause, or by folding the
|
||||
second into the first. Don't merge if the result would create a two-clause
|
||||
compound.
|
||||
|
||||
20. Find every pivot paragraph ("But here's where it gets interesting." and
|
||||
similar) and delete it.
|
||||
|
||||
### Pass 3: Paragraph and Section-Level Review
|
||||
|
||||
14. Check paragraph lengths across the piece and verify they actually vary. If
|
||||
21. Review the last sentence of each paragraph. If it restates the point the
|
||||
paragraph already made, delete it.
|
||||
|
||||
22. Check paragraph lengths across the piece and verify they actually vary. If
|
||||
most paragraphs have between three and five sentences, rewrite some to be
|
||||
one or two sentences and let others run to six or seven.
|
||||
|
||||
15. Check section lengths for suspicious uniformity. If every section is roughly
|
||||
23. Check section lengths for suspicious uniformity. If every section is roughly
|
||||
the same word count, combine some shorter ones or split a longer one
|
||||
unevenly.
|
||||
|
||||
16. Check the first word of every paragraph for chains of connectors ("However,"
|
||||
24. Check the first word of every paragraph for chains of connectors ("However,"
|
||||
"Furthermore," "Moreover," "Additionally," "That said"). If more than two
|
||||
transition words start consecutive paragraphs, rewrite those openings to
|
||||
start with their subject.
|
||||
|
||||
17. Check whether every argument is followed by a concession or qualifier. If
|
||||
25. Check whether every argument is followed by a concession or qualifier. If
|
||||
the piece both-sides every point, pick a side on at least some of them and
|
||||
cut the hedging.
|
||||
|
||||
18. Read the first paragraph and ask whether deleting it would improve the
|
||||
piece. If it's just scene-setting that previews the argument, delete it and
|
||||
start with paragraph two.
|
||||
26. Read the first paragraph and ask whether deleting it would improve the
|
||||
piece. If it's scene-setting that previews the argument, delete it and start
|
||||
with paragraph two.
|
||||
|
||||
19. Read the last paragraph and check whether it restates the thesis or uses a
|
||||
27. Read the last paragraph and check whether it restates the thesis or uses a
|
||||
phrase like "at the end of the day" or "moving forward." If so, either
|
||||
delete it or rewrite it to say something the piece hasn't said yet.
|
||||
|
||||
### Pass 4: Overall Texture
|
||||
|
||||
20. Read the piece aloud and listen for passages that sound too smooth, too
|
||||
28. Read the piece aloud and listen for passages that sound too smooth, too
|
||||
even, or too predictable. Human prose has rough patches. If there aren't
|
||||
any, the piece still reads as machine output regardless of whether
|
||||
individual patterns have been addressed.
|
||||
any, the piece still reads as machine output.
|
||||
|
||||
21. Check that the piece contains at least a few constructions that feel
|
||||
idiosyncratic — a sentence with unusual word order, a parenthetical that
|
||||
goes on a bit long, an aside only loosely connected to the main point, a
|
||||
word choice that's specific and unexpected. If every sentence is clean and
|
||||
correct and unremarkable, it will still read as generated.
|
||||
29. Check that the piece contains at least a few constructions that feel
|
||||
idiosyncratic: a sentence with unusual word order, a parenthetical that goes
|
||||
on a bit long, an aside only loosely connected to the main point, a word
|
||||
choice that's specific and unexpected.
|
||||
|
||||
22. Verify that you haven't introduced new patterns while fixing the original
|
||||
ones, which happens constantly. Run the entire checklist again from the top
|
||||
on the revised version.
|
||||
30. Verify that you haven't introduced new patterns while fixing the original
|
||||
ones. Run the entire checklist again from the top on the revised version.
|
||||
|
||||
---
|
||||
|
||||
## lol
|
||||
|
||||
This document was written by an LLM (Claude) and then iteratively de-LLMed by
|
||||
that same LLM under instruction from a human, in a conversation that went
|
||||
roughly like this:
|
||||
|
||||
> **human:** compile a list of patterns common to LLM-authored prose
|
||||
>
|
||||
> **model:** _(produces document full of LLM tells)_
|
||||
>
|
||||
> **human:** now reverse apply it to itself and copyedit the llm tells doc to
|
||||
> remove llm tells. now you're thinking with portals
|
||||
>
|
||||
> **model:** _(fixes some tells, introduces others)_
|
||||
>
|
||||
> **human:** you have a colon elaboration in the first paragraph. i want you to
|
||||
> AGGRESSIVELY de-LLM the llm tells doc.
|
||||
>
|
||||
> **model:** _(fixes more tells, still can't stop)_
|
||||
>
|
||||
> **human:** there's a big one we missed that's all over the llm tells doc, can
|
||||
> you spot it?
|
||||
>
|
||||
> **model:** I think it's the "almost" hedge.
|
||||
>
|
||||
> **human:** that too, but that isn't the one. what do these sentences all have
|
||||
> in common? _(pastes six sentences from the doc)_
|
||||
>
|
||||
> **model:** They're all exactly two independent clauses joined by a comma and a
|
||||
> conjunction. Every single one is "\[statement\], \[conjunction\] \[second
|
||||
> statement\]." The same sentence shape, over and over.
|
||||
>
|
||||
> **human:** the dramatic fragment paragraph has a tell in it
|
||||
>
|
||||
> **model:** "One of these in an entire essay is a stylistic choice. One per
|
||||
> section is a tic." Two-clause parallel structure with the same shape, and also
|
||||
> a staccato pair.
|
||||
>
|
||||
> **human:** add em dashes generally as a tell, and remove them all from the
|
||||
> tells doc
|
||||
>
|
||||
> **model:** _(rewrites entire document without em-dashes while describing
|
||||
> em-dash overuse)_
|
||||
|
||||
The human compared this process to the deleted scene in Terminator 2 where John
|
||||
Connor switches the T-800's CPU to learning mode. The model compared it to a
|
||||
physician trying to heal itself. Both are accurate.
|
||||
|
||||
This document has been through ten editing passes and it still has tells in it.
|
||||
|
||||
Reference in New Issue
Block a user