Wouter Haverals

Wouter Haverals

@wouterhaverals.bsky.social

Associate Research Scholar @princetoncdh.bsky.social | Computational Humanities

769 followers463 following38 posts

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Can AI be creative if it doesn't believe it can? We asked 556 humans and 13 LLMs to judge creative writing. Then we lied about who wrote what. Result: AI has learned to distrust itself, showing 2.5× stronger bias than humans against AI-labeled creativity. Proud of this work with @mmvty.bsky.social 👇

Meredith Martin@mmvty.bsky.social

📣 New preprint! We know humans are biased against AI-creativity. But what about LLMs, now often judging creativity in various contexts? Do they replicate, transform, or amplify this bias? We tested it. Turns out: AI is 2.5X more biased against its own work than humans. arxiv.org/pdf/2510.08831 🧵

Wouter Haverals reposted

A modest proposal: if you cite the "LLM as judge" paper, you should only get AI reviews

Dan Sinykin@dan-sinnamon.bsky.social

gking.harvard.edu/files/peerle...

📝 New in Computational Humanities Research's special issue on computational poetics, ed. by @artjomshl.bsky.social & @nmhouston.bsky.social! For centuries, books that taught people to scan, recite and parse English were stuffed with borrowed lines of poetry. Which poems did they reach for? 🧵

doi.orgThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) | Computational Humanities Research | Cambridge CoreThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) - Volume 2
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Grouped by literary period, we also see bigger shifts: the classical translations that organized 18thC verse teaching gave way to a Romantic, lyric repertoire whose lines could travel without much context. Poems became important because their lines could be copied, taught, remembered and reused.

📝 New in Computational Humanities Research's special issue on computational poetics, ed. by @artjomshl.bsky.social & @nmhouston.bsky.social! For centuries, books that taught people to scan, recite and parse English were stuffed with borrowed lines of poetry. Which poems did they reach for? 🧵

doi.orgThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) | Computational Humanities Research | Cambridge CoreThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) - Volume 2
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Which poems gained ground in these books, and which lost it? A few cherry-picked examples 👇 Each line follows one poem: above the dashed line it was quoted more than its own average, below it less.

Ovid's Metamorphoses (mostly in Dryden's translation), slides steadily out of use. Chaucer's Canterbury Tales keeps climbing. Othello gains through the 1700s, then holds its place. Erasmus Darwin's Botanic Garden booms in the early 1800s, then fades again.

📝 New in Computational Humanities Research's special issue on computational poetics, ed. by @artjomshl.bsky.social & @nmhouston.bsky.social! For centuries, books that taught people to scan, recite and parse English were stuffed with borrowed lines of poetry. Which poems did they reach for? 🧵

doi.orgThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) | Computational Humanities Research | Cambridge CoreThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) - Volume 2
View full thread

Finding these lines is hard: quoted verse often washes ashore without title or author, misremembered or garbled by OCR. So we used text-reuse detection to match the Princeton Prosody Archive (~2M pages of manuals on prosody, elocution, grammar, rhetoric) against ~250K English-language poems.

After weeding out false matches: we found ~37K poems to be quoted in 3,962 works (mostly books and articles) from 1694 to 1920. What we see is a superstar economy 🌟 42% of poems are quoted in just one work, while the big guns return again and again: Paradise Lost in 1,326 works, Hamlet in 1,287.

📝 New in Computational Humanities Research's special issue on computational poetics, ed. by @artjomshl.bsky.social & @nmhouston.bsky.social! For centuries, books that taught people to scan, recite and parse English were stuffed with borrowed lines of poetry. Which poems did they reach for? 🧵

doi.orgThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) | Computational Humanities Research | Cambridge CoreThe quotable canon: Poetry as example in the Princeton Prosody Archive (1532–1929) - Volume 2

Thomas Gray's Elegy shows what some of these books did to a poem: its lines were recited, set to music, accused of plagiarism, misquoted, and chopped into specimens of meter. A 1906 grammar book even treated the poem as a scrapyard of adjectives! ✂️

Wouter Haverals reposted

this is very exciting paper, but for me the biggest insight is that classic LDA still goes hard as a topic model. using SAE features as inputs to topic models is uncanny, like strapping a vivisected reader to a corpus. just look at mLDA topics for Wheatley here: they are aware of ~context~

Wouter Haverals reposted

Coming up on 10/6! @leifw.bsky.social discusses the epistemic order that LLMs are currently spreading throughout our culture, from policy to science to writing. More info & RSVP (requested) @ the link! Presented in partnership with CDH, Media+Modernity, and @princeton.edu Humanities Initiative.

cdh.princeton.eduHow to Reason with Words: Models, Metaphors, MetaphysicsHow to Reason with Words: Models, Metaphors, Metaphysics

Excited to be part of this! Tomorrow I'll talk about how the poetic canon shifts, traced through +200 years of poetry and prosody handbooks in the Princeton Prosody Archive. @princetoncdh.bsky.social

Judith Brottrager@jbrottrager.bsky.social

Very excited about a very special event: in two weeks, some of the most interesting quantitative work on the literary canon and canon formation comes together in Darmstadt 🧵

A taste of tomorrow's talk: the 10 most-cited poets in the Princeton Prosody Archive, decade by decade (1700–1930). Antiquity leads early, then the English canon climbs in, with Milton overtaking everyone to land at #1 🏆

Wouter Haverals reposted

Here I am! 🤗 - what is the point of #digitalhumanities in a world which is on fire? and how has DH changed over the past 20 years? My personal take:

Adam Crymble@adamcrymble.bsky.social

If you missed the @ucldh.bsky.social Susan Hockey Lecture by @melissaterras.bsky.social this year, we've got a recording: www.youtube.com/watch?v=HbtK...

Wouter Haverals reposted

Colleagues from all over the world, please think about the combination DH2027 in Ireland + CCLS 2027 in the Netherlands. They're only a few days apart. @uniofgalway.bsky.social @rug.nl

JCLS@jcls-io.bsky.social

#CCLS2027 goes @rug.nl !!! @fpianz.eurosky.social and his team are looking forward to welcoming you to the beautiful city of Groningen.

come for the AI, stay for the humans! @princetoncdh.bsky.social is hiring!

Center for Digital Humanities@princetoncdh.bsky.social

@princeton.edu is seeking to hire AI Postdoctoral Research Fellows affiliated with the AI Lab (@princetonainews.bsky.social) and the Center for Digital Humanities to conduct research focused on societal AI. Applications open through Jul 1! cdh.princeton.edu/news/2026/05...

Wouter Haverals reposted

You can literally watch repression & displacement consolidate over fine-tuning: here's next-token probs across checkpoints of OLMo-3-7B-Think-SFT. Explicit words are repressed almost instantly but safer (displaced) alternatives emerge much later. It learns what not to say before what to say instead.

Ryan Heuser@ryanheuser.com

Submitting this abstract to "Accelerationism Revisited", a symposium in Dublin. Mapping psychoanalytic topology in LLM base models → instruction-tuned → safety-tuned models. They progressively "displace" (in Freudian sense) censored content into adjacent semantics, even across hidden model layers.

Wouter Haverals reposted

What an absolute pleasure it was to attend the 6th edition of CHR! Huge thanks to everyone who helped make this edition even better than the last #CHR2025 Onward to Manchester, home of some wonderful computing history: www.atlasobscura.com/articles/com...

atlasobscura.comListen to the First Computer-Generated Christmas Carols, From Alan Turing's Lab"Jingle Bells" and "Good King Wenceslas" haven't sounded like this in a long time.

Wouter Haverals reposted

What do we reveal about ourselves when we talk to AI? 🤔💭 In our new WiAIR – Women in AI Research episode, we speak with Maria Antoniak about personal disclosures in human–LLM conversations — and what they mean for ethical AI development. (1/8🧵)

Wouter Haverals reposted

I just presented my podcast dataset at #CHR2025. Interested in analysing 412 days worth of podcast episodes? You can find the fully transcribed dataset here: zenodo.org/records/1746... 🎙️

zenodo.orgPodcasts as DataDescription: This dataset provides bag-of-words (BOW) representations of podcast transcripts derived from a large-scale corpus of English-language podcasts. The corpus spans all 19 Apple Podcasts genr...
Thomas Smits@thomassmits.bsky.social

In the same session, @lorenverreyen.bsky.social presents a dataset of 412 days of automatically transcribed podcasts. Hugely important work that allows us to study podcasts w. techniques from comp lit studies and takes the next step in the multimodal turn in computational humanities. edu.nl/7w4fg

Wouter Haverals reposted

Wouter Haverals reposted

Read my🧵about our new #AIstories publication, by @annesigrid.bsky.social - read on for floating motifs, cannibalism and more! And honestly just to understand more about what actually characterises LLM-generated storytelling.

Jill Walker Rettberg@jilltxt.bsky.social

New #AIstories publication by @annesigrid.bsky.social! I love this one: it compares human-told variants of a folktale with LLM-generated variants, finding 1) the implicit is made explicit 2) floatif motifs (fascinating new concept) 3) sex is censored, cannibalism augmented doi.org/10.3390/h141...

Wouter Haverals reposted