David Mimno

David Mimno

@dmimno.bsky.social

He teaches information science at Cornell. http://mimno.infosci.cornell.edu

7K followers4.7K following868 posts

Pinned

Optimist: AI has achieved human level performance! Realist: “AI” is a collection of brittle hacks that, under very specific circumstances, mimic the surface level of human intelligence Pessimist: AI HAS achieved human level performance

David Mimno reposted

NEW PREPRINT: Cheap AI-Assisted Reverse Engineering and What It Will Do (in submission) We argue that AI coding tools make it easy, cheap, and fast to reverse engineer software and hardware—and IP law is not prepared for this challenge. arxiv.org/abs/2610.35633

arxiv.orgCheap AI-Assisted Reverse Engineering and What It Will DoGenerative AI is putting the law of reverse engineering (RE) under severe strain. Existing IP and technology laws assume that RE is expensive and time-consuming, and that it requires specialized exper...

Side benefit of this idea: I can direct prospectives to less established faculty they might not be aware of

Mor Naaman@informor.bsky.social

Show proof that you aren't just spamming. Crazy idea: put on your webpage a list of professors that you contact; no more than 10-15 names. Refer to it in your email. Those names better be in an area close to mine. This is an assessment signal of interest/commitment in me AND the research area.

David Mimno reposted

David Mimno reposted

We are hiring!! "Artificial intelligence, broadly construed. This includes embodied AI and robotics, machine learning and the systems that support it, and AI developed for problems in science, engineering, medicine, education, and society." jobs.wisc.edu/jobs/assista...

jobs.wisc.eduAssistant / Associate / Full Professor of Computer Sciences - Madison, Wisconsin, United StatesCurrent Employees: If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.Job Category:FacultyEmployment Type:Regula...

David Mimno reposted

Fun thing! I'm looking at a copy of a book of summaries of Aristotle’s natural philosophy (Naturalis totius philosophiae paraphrases (1538)), and the book has a semi-circle mirror set into the backboard. Has any one seen this elsewhere? What's going on? A device to connect up with the Aristotle?

David Mimno reposted

Book launch today! My new book, "Why You Should Read More Fiction" (Johns Hopkins), is part of a wave of digital humanities work that explains why reading fiction is so important for our minds, especially right now. I hope you'll pick up a copy and spread the word. #digitalhumanities #fiction

David Mimno reposted

David Mimno reposted

🚨 [Token][ization] Paper Alert 🚨 Tokenization is a wildly understudied area of language modeling despite it having effects across all of NLP. Over the past ~8 months, 32 (!) tokenizer researchers put together the most comprehensive survey of the field. Check it out!

David Mimno reposted

In 2023, Change.org integrated an AI-assisted writing tool into their platform. We found that access to the tool changed platform trends in petition text, but that outcomes (signatures and comments) did not improve... Excited that this paper is out, check it out! 🔗: www.nature.com/articles/s41...

nature.comIntroducing AI to an online petition platform changed outputs but not outcomes - Nature Human BehaviourCorpus et al. examine how the introduction of an AI writing tool impacted Change.org petitions, finding that it increased petition homogeneity but did not improve petition outcomes.
Isabel Silva Corpus@isabelcorpus.bsky.social

Excited to share a new working paper! What happened when Change.org integrated an AI writing tool into their platform? We provide causal evidence that petition text changed significantly while outcomes did not improve. 1/ arxiv.org/abs/2511.13949

David Mimno reposted

If you're at #COLM2026, come check out our poster for "Spoiler Alert" (arxiv.org/abs/2604.09854). We ask why LLM fiction is so bad at holding narrative tension, and create a metric to measure tension in short stories. What improves LLM fiction on this metric, it turns out, is narrative planning.

Sparsity is back! Sparsity is everywhere in language, but managing it requires overhead. For the last ~15 years it was faster to just do the dense operation, knowing most of it was useless. That sparse operations work is a huge shift in the "do something clever" vs. "spend more money" tradeoff.

mr. TIM@timkellogg.me

NanoGPT pretraining runs now take 39.9 seconds for a 124M model(!!) now, 124M is *tiny* so it might not seem relevant. But much of the gains in LLM pretraining are data quality and a great way to find quality data is to train on it & measure the lift

"Will no agents rid me of this turbulent priest?"

Ethan Mollick@emollick.bsky.social

The cybersecurity threat from agents is increasingly more likely to come from a massed swarm of AIs whose only goal is to penetrate your system to figure out how much you paid for your company t-shirts as part of a research effort to "find good t-shirt prices" as it is from bad actor attacks.

David Mimno reposted

Models like Talkie-1930 sound like voices from the past. If they could reliably speak from specified historical vantage points, researchers might also use them to simulate the past. But how reliable are they? Today we release a benchmark answering that question for English contexts 1831-1930.

It's possible for Jev/Laya/Decision Models to be not that big a deal as tech and massive as a new paradigm. Here's why I'm really excited from an NLP history perspective (thread)

View full thread

And I'm going to bet that a lot of what AI companies imagined as the potential exponential-growth big-model use cases aren't writing code or emails, but automating business processes. And Jev/Laya/whatever-comes-next are going to make that vastly simpler and cheaper.

Are they groundbreaking technically? Probably not. I'm sure there's training tricks, but everyone will figure them out. But as a new *design pattern* for how models are used, this feels totally different and BERT-level exciting.

It's possible for Jev/Laya/Decision Models to be not that big a deal as tech and massive as a new paradigm. Here's why I'm really excited from an NLP history perspective (thread)

View full thread

Sometimes you need text output, especially for code. But a lot of the time we're just trying to get a simple 👍👎 for some fairly complicated question from a lot of documents. The hard part is often specifying the problem, which usually ends up looking like a flowchart.

That's where a model optimized for making simple decisions from complex inputs is so exciting. Clear answers, fast cheap inference, and compatible with the kind of sequence-of-decisions logic we were already moving towards. Every project we're working on can use this.

It's possible for Jev/Laya/Decision Models to be not that big a deal as tech and massive as a new paradigm. Here's why I'm really excited from an NLP history perspective (thread)

View full thread

In the past few years, text generation models have become good enough that you can do structured prediction purely as a text gen process: the text that the model generates just happens to be a JSON object that happens to be the structure. No cleverness beyond clear specification, no custom code.

This is great! And it's so flexible and effective that we've started to assume that everything is just a text generation problem. But besides being ruinously slow and expensive, just figuring out what the answer was in the generated free text becomes its own hard problem.

It's possible for Jev/Laya/Decision Models to be not that big a deal as tech and massive as a new paradigm. Here's why I'm really excited from an NLP history perspective (thread)

View full thread

This was a big leap, but still required a lot of cleverness in constructing the mapping, and custom code to train and run. Moving to a new task meant starting mostly from scratch.

After 2013, word2vec embeddings started making the classifiers work better. Contextualized embeddings (ELMo, BERT) were even better, but still just fed vectors into stacks of classifiers.

It's possible for Jev/Laya/Decision Models to be not that big a deal as tech and massive as a new paradigm. Here's why I'm really excited from an NLP history perspective (thread)

Around 2010, the most exciting approaches were clever ways to map complex structured prediction tasks into huge numbers of tiny decisions, usually performed with single-layer linear classifiers. For example, shift-reduce parsers phrased parsing as a four-way choice made at each token.

David Mimno reposted

We have a new paper on AI debunking that includes a bunch of interesting data on various "epistemically suspect beliefs". Check it out!

Esther Boissin@boissinesther.bsky.social

Happy to share a new preprint with @tomcostello.bsky.social, @dgrand.bsky.social and @gordpennycook.bsky.social 🧵 "What beliefs are most debunkable?" osf.io/preprints/ps... We investigate the characteristics of the beliefs that are (or are not) influenced by counterevidence in 3,341 AI dialogues.

David Mimno reposted

Prospective PhD students: if you work on computational humanities, cultural analytics and/or cultural AI, pls apply to Duke English! We're recruiting in these areas & you'd join a vibrant community. Candidates with training in both lit studies + CS/sciences esp welcome. Email me if any questions!

A university founded in the Middle Ages in a city that centers itself around a Medieval castle does not see a need to study Medieval History

Margot Finn@eicathomefinn.bsky.social

Celtic (UG), Chinese & Russian (UG), Contemporary History, Economics & Statistics (joint degree), Inclusive Education (MSc), Intellectual History, Italian & Classics (joint), Law & Social Policy (joint), Medieval History, Persian Studies (UG), Portuguese (UG), Psychology & Economics (joint)....

I’d check kalshi

Ethan Mollick@emollick.bsky.social

I don’t usually share rumors but: 1) This is from someone with inside knowledge & is plausible 2) Is a real issue of policy we need to think about: if the norms of sharing become strained, will the labs start hoarding knowledge to avoid PR or regulatory issues? scottaaronson.blog?p=10062

David Mimno reposted

The silence from industry in the face of concerted attacks on US competitiveness has been disgraceful. Will this finally wake them up? Or will they just offshore all skilled work? And yes, this is a constitutional crisis if the executive can apply a “ridiculous fee” veto to any legislation.

Michael Clemens@mclem.org

The US President's new proposal to tax international students has been approved by the White House for release this week. It's an unprecedented $100,000 tax on int'l grads who stay to work after graduation on Optional Practical Training (most grads do), a crucial bridge to remaining by any channel.

The silence from industry in the face of concerted attacks on US competitiveness has been disgraceful. Will this finally wake them up? Or will they just offshore all skilled work? And yes, this is a constitutional crisis if the executive can apply a “ridiculous fee” veto to any legislation.

Michael Clemens@mclem.org

The US President's new proposal to tax international students has been approved by the White House for release this week. It's an unprecedented $100,000 tax on int'l grads who stay to work after graduation on Optional Practical Training (most grads do), a crucial bridge to remaining by any channel.