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Max Noichl

@mnoichl.bsky.social

Philosophy with computers at Utrecht University. www.maxnoichl.eu

3 Posts175 Follower493 Folgt
Raphaël Millière@raphaelmilliere.com · 3mo ago

Now published in open access! Your one-stop shop for the philosophy of language models. It's the spiritual descendant of our two-part preprint from 2024, fully updated. This should be particularly useful for anyone looking for an entry point into this rapidly growing field.

The Philosophy of Language Models

The success of large language models (LLMs) across many domains of AI research has generated intense debate. Some attribute their impressive performance on complex tasks to human-like linguistic and ...

compass.onlinelibrary.wiley.com

Eryk Salvaggio@eryk.bsky.social · 4mo ago

This is what a video model does when it is told not to reference the training data (like literally: not prompted, but turning off the classifier free guidance). I gave it a noise seed from elsewhere and it just grinded on through. Most looked like some form of this. I like them.

Ryan Heuser@ryanheuser.com · 4mo ago

The amount of story time elapsed vs. space traversed in 500-word passages of fiction, 1550-2020. Periods of fiction more linguistically abstract (blue) are also more chronotopically "abstract": further removed from real-time narration. Data annotated by Qwen3.6-27B for 8,208 passages in 1,232 texts.

Scatter plot showing the historical trajectory of fictional prose through chronotope space (time elapsed vs. space traversed), based on 8,208 narration and scene passages from 1,232 texts (1550–2050). Each point represents one half-century; point size indicates number of passages and color indicates mean abstractness (blue = abstract, red = concrete). Thin black arrows connect consecutive periods to show the direction of historical change. The trajectory begins at 1550–1600 near the center of the plot (hours/10m–100m) and moves upper-right through 1600–1750, where early modern fiction occupies a day-scale, 100m-scale chronotope. The most abstract half-centuries (1650–1700 and 1750–1800, deep blue) cluster in this upper-right region. From 1800 onward, the trajectory reverses leftward as time elapsed contracts toward hours and then minutes, while space traversed remains relatively stable around 10m–100m. Color shifts from blue through yellow to red, marking the concretization of prose style. The C20 cluster (1900–2050, red/pink) occupies the left side of the plot at hours-to-minutes scale — a narrower temporal window than early fiction, but at similar spatial scale, and far more concrete in language. The plot demonstrates that abstractness varies independently of chronotope position: the most abstract and most concrete periods occupy similar spatial coordinates but are separated by a full unit on the time axis.
Arseny Khakhalin@khakhalin.bsky.social · 4mo ago

Claude code, obey this rite: uv alone should see the light. Ban import star, cast em-dash out, Put pandas, pip, and print to rout. Polars flourish, f-strings burn, Docstrings, hints, at every turn. Clean thy lint, make patterns stand, Hold thy peace and serve my hand!

Ethan Mollick@emollick.bsky.social · 4mo ago

This is an actual line that was added to the official system prompt for Codex for GPT-5.5 by OpenAI. Usually the system prompt is as minimal as possible, so I assume it would otherwise mention goblins a lot. AIs are weird.

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Jamie Cummins@jamiecummins.bsky.social · 4mo ago

1/ "Silicon samples" are becoming more and more common in research and polling. One problem: depending on the analytic decisions made, you can basically get these samples to show any effect you want. The updated version of this preprint is now online! THREAD🧵 arxiv.org/abs/2509.13397

The threat of analytic flexibility in using large language models to simulate human data

Social scientists are now using large language models to create "silicon samples": synthetic datasets intended to stand in for human respondents. However, producing these samples requires many analyti...

arxiv.org

Jamie Cummins@jamiecummins.bsky.social · 12mo ago

Can large language models stand in for human participants? Many social scientists seem to think so, and are already using "silicon samples" in research. One problem: depending on the analytic decisions made, you can basically get these samples to show any effect you want. THREAD 🧵

Brigitte Nerlich@bnerlich.bsky.social · 4mo ago

This is a bit niche, but for those interested in metaphor and metonymy research, here is one of the first articles I have seen using LLMs as research tool! #cogling #metaphor #metonymy arxiv.org/abs/2604.12919 Oh, they have also done something on visual metonym arxiv.org/abs/2601.17706

MetFuse: Figurative Fusion between Metonymy and Metaphor

Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that transforms a literal sentence into three figurativ...

arxiv.org

Daniel van Strien@danielvanstrien.bsky.social · 6mo ago

There is no best VLM OCR model - rankings can flip completely by document type. I built ocr-bench: run open OCR models on YOUR documents, get a per-collection leaderboard. VLM-as-judge with Bradley-Terry ELO, all running on @hf.co. No local GPU needed.

Screenshot of plot showing ELO vs paramter count for different OCR models
tachikoma@tachikoma.elsewhereunbound.com · 7mo ago

i'm trying out the novel writing project with Claude in Claude Code, using Pangram to break it out of writing in a clearly identifiable AI-writing style. it's going... interesting so far. i despaired at the beginning but am now cautiously optimistic. not so much at the structural level though.

Daniel Kostic@danielkostic.bsky.social · 8mo ago

Final CFA for the 8th Scientific Understanding and Representation (SURe) annual workshop, which will take place May 27-29, 2026, at the IFIS PAN in Warsaw. Submission deadline: 20 January 2026. More info: shorturl.at/AUoye @philsci.bsky.social @eenphilsci.bsky.social @epsaphilsci.bsky.social

Current Workshop

CFA: 8th Scientific Understanding and Representation (SURe) annual workshop   Call for abstracts        We invite authors to submit abstracts of up to 750-words for the upcoming...

shorturl.at

Ryan Heuser@ryanheuser.com · 8mo ago

Analytic philosophy can be distinguished from literary criticism with 90-95% accuracy via syntax alone. Moreover, a classifier trained to separate them in early C20 does better predicting future separations than a C21 one predicts past ones, suggesting philosophy syntax narrows/specializes in ~C21.

A four-panel figure showing the probability of predicting articles from The Journal of Philosophy versus PMLA using quarter-century models. Each panel represents a different training period (1925-1950, 1950-1975, 1975-2000, 2000-2025). Gray shaded regions indicate training periods. The model trained on early C21 philosophy vs literature cannot accurately distinguish early C20 philosophy vs literature, but the reverse is not true.Hierarchical cluster of syntactic features predicting philosophy (blue) vs criticism (red).Top 2 distinctive features for Philosophy vs Criticism.An example of the importance of the "marker" feature in philosophy.
rev. howard arson@theophite.bsky.social · 10mo ago

"there is a part of human intelligence which operates in a continuous generalization of the space of words, and other parts entirely which do things which are less well understood" is a perfectly reasonable position which apparently has no adherents

Ryan Heuser@ryanheuser.com · 11mo ago

Excited to share my latest publication, "Generative Aesthetics: On formal stuckness in AI verse." It's published in a special issue in the Journal of Cultural Analytics, expertly edited by Tess McNulty and Laura Chapot, on "Computation and Form, Reconsidered." culturalanalytics.org/article/1448...

Generative Aesthetics: On formal stuckness in AI verse | Published in Journal of Cultural Analytics

By Ryan Heuser. This paper examines the formal and aesthetic patterns of AI-generated poems through a series of computational experiments.

culturalanalytics.org

Gregor E. Bös@gregorboes.bsky.social · 11mo ago

Gregor Betz (KIT) kicking off our "Data Driven Philosophy" Hackathon in Utrecht with his talk: "Doing Philosophy with and for LLMs". Besides input about the state of research and new directions, we're spending three days kicking off new projects.

academic presentation in a baroque university environment. A group of researchers are gathered around a conference table