Maria Antoniak

@mariaa.bsky.social

NLP, cultural analytics. Assistant Professor of CS at University of Colorado Boulder. Books, bikes, games, art. https://maria-antoniak.github.io

I like these suggestions also for ARR and NLP conferences! Keep the rebuttal and score updates, remove the discussion, penalize reviewers who don’t update their scores.

Victor Escorcia@escorciav.bsky.social · 22h ago

Ok & kudos to @neuripsconf.bsky.social PCs 💪🏼 Diversity of trials is the best way to test what works & not. I doubt that any AI venue can claim to have nailed peer review at scale. Otherwise social media during review release & decision period would be 🌈💐

may be time to resurface this <squints> ten year old FATML paper that explored the ethics of automatic experimentation, say by agents. 841.io/doc/ethics-o...

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Alexandra Lahav@alahav.bsky.social · 2h ago

New @bloomberglaw.com article by Olivia Carville - TikTok experimented on users, putting 10% (about 15M people) in a "filter bubble" exposing them to repetitive content that the algorithm thought they wanted, but was toxic. If you want to know why these cases are going to be massive...

E.g., our reasoning work here: academic.oup.com/pnasnexus/ar... shows how (even much older) models and humans make similar patterns of trading off between logic and semantic biases that can roughly be interpreted as "using prior knowledge. 3/

Language models, like humans, show content effects on reasoning tasks

Abstract. Abstract reasoning is a key ability for an intelligent system. Large language models (LMs) achieve above-chance performance on abstract reasoning

academic.oup.com

as we get further into the end of days, I'm reminded about how much of research taste, values and judgment is bound up in the taste, values and judgment of small communities of researchers

📣 I am hiring a 𝗣𝗼𝘀𝘁𝗱𝗼𝗰 𝗶𝗻 𝗦𝗼𝗰𝗶𝗮𝗹 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗛𝘂𝗺𝗮𝗻-𝗔𝗜 𝗛𝘆𝗯𝗿𝗶𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 📍 Berlin 📅 3-year position 💡 Ideal for researchers with a PhD in Computer Science, Cognitive Science, Applied Math, Physics, etc. and a strong background in AI, RL, and computational social science. Details below

Postdoctoral Fellow in Social Reinforcement Learning and Human-AI Hybrid Systems - Max-Planck-Institut für Bildungsforschung

The Center for Humans and Machines (CHM) at the Max Planck Institute for Human Development in Berlin conducts interdisciplinary science to understand, anticipate, and shape major disruptions from A...

careers.mpib-berlin.mpg.de

There are two wolves. One always lies. One controls the lever of trolley track. They're in a state of superposition inside a box. On the trolley are infinite monkeys at infinite typewriters going to an infinite hotel. The trolley must first travel halfway, but before that a quarterway, and so on...

"We're all worried," as what it means to do research (in my field, Theoretical CS) seems to be shifting, and shifting fast. What to do? Senior researchers must lead by example, knowing that not everything will pan out. What I'm suggesting below may not work everywhere, but here's my own advice: 1/

Some initial thoughts, and a complicated mix of feelings. Wow. I mean, Erdos problems are cool (I genuinely mean that), I didn't know about the Jacobian conjecture before it got disproved. But this newest batch from OpenAI hits home in a way the previous announcements did not.

“…[COLM] may have to narrow the scope of allowed contributions. Theoryslop and slopterpretability are hard to manage in the same review process as other papers.” I recognize these categories, but the idea of punishing all theory and framework papers is tough. Agreed on more desk rejections.

Conference on Language Modeling@colmweb.org · 5d ago

📢 New blog post describing the COLM 2026 PCs’ analyses of AI use in submitted papers. gregdurrett.github.io/colm2026-blo... (temporary home, new COLM website coming soon!)

Title and first few paragraphs of the blog post "AI submissions at COLM: theoryslop, slopterpretability, and papers in the age of agents"

If you're going to cite that NBER report from OpenAI about "how people use AI," you've got to at least caveat it. We have no way to directly verify most of the report, and we do have at least one good reason, via indirect evidence and quoted below, to not trust it. www.nber.org/papers/w34255

Maria Antoniak@mariaa.bsky.social · 7mo ago

Not the point of the OP, but I was curious and took a closer look at this 2025 piece from OpenAI. Much could be said, but it fails my go-to test for all of these pieces about "how people actually use AI": the tokens "sex" "erotic" and "NSFW" do not appear in the paper.

“…our sense that we are reading the work of another human being, someone with connections to others, to a time and a place like postwar Naples, someone to whom we might relate our own life stories, is our strongest reason not to cede too much ground to AI-generated text.”

Dan Cohen@dancohen.org · 6d ago

New issue of my newsletter Humane Ingenuity: “The Breath of the Author” — The palpable presence of someone else’s mind in our best writing should give us pause about the encroachment of AI text newsletter.dancohen.org/archive/the-...