iiinova — where your digital self keeps evolving

Reposted by Navita Goyal

Jenna Russell @jennarussell.bsky.social · 01/10/2026

How much is an AI token worth? We fit scaling laws to find out! In August 2026, Pangram labels 31% of FineWeb-filtered web tokens as AI-generated, up from 10% in June 2024. We pretrained 800 LMs (19.9M–973M params) on mixes of human and AI web text to measure what it does to pretraining 🧵

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Navita Goyal @navitagoyal.bsky.social · 25/08/2026

If you're also excited about principled interpretability frameworks and tools, this workshop is for you! Please submit your work to the workshop at openreview.net/group?id=Neu.... 🚨 Submission deadline extended to Sept 1 (AoE).

interpscience.github.io

Call for Papers · Interpretability as a Science

Call for papers for the Interpretability as a Science workshop at NeurIPS 2026.

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UMD Science @umdscience.bsky.social · 12/08/2026

How can we give people more agency when interacting with artificial intelligence systems? That is one of the questions that Sarah Wiegreffe's research aims to answer. Ask Sarah your questions about natural language processing, empirical ML and explainable #AI in today's #RedditAMA: redd.it/1vm665h

Sarah Wiegreffe holding a laptop in a hallway, standing next to a red pillar with binary code and words such as "machine learning" and "theory" on it

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Navita Goyal @navitagoyal.bsky.social · 03/08/2026

📣 We are organizing the first InterpScience Workshop @ NeurIPS 2026 in Sydney! The goal of the workshop is to build a more rigorous scientific foundation of LLM interpretability. 📝 Papers due: Aug 28 🌐 interpscience.github.io ✉️ interpscience@gmail.com [1/7]

interpscience.github.io

Interpretability as a Science · Workshop

What can interpretability learn from other sciences? A NeurIPS 2026 workshop toward rigorous foundations for understanding LLMs.

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Sayash Kapoor @sayash.bsky.social · 07/07/2026

Thrilled to share that I am joining UC Berkeley as an Assistant Professor in the School of Information! I start in Fall 2027, and I am recruiting PhD students this cycle. List me in your application if you want to work with me! More on what I'm looking for (and a form to indicate interest) 🧵

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Yonatan Belinkov @boknilev.bsky.social · 17/06/2026

Are you wondering if LLM interpretability results generalize, reproduce, etc.? Check out the reproducibility challenge and submit your work reproducing papers in this area: bsky.app/profile/blac...

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Naomi Saphra @nsaphra.bsky.social · 15/06/2026

We don’t always know what problems are hard for LLMs. So devs evaluate on tasks HUMANS find hard or on broad benchmarks. What if we could instead anticipate which scenarios a model will fail on—all without evaluating specific input examples? 🧵NEW PAPER by @jenniferlumeng.bsky.social

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Navita Goyal @navitagoyal.bsky.social · 27/03/2026

Thanks WiAIR (@wiair.bsky.social‬) for featuring my work on your YouTube channel. Watch the video to hear about our work on inference-time steering — and why these interventions LLMs may not be as “precise” as they look.

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Yoav Artzi @yoavartzi.com · 17/02/2026

This call is still open. I am looking to recruit, as well as many other faculty at Cornell. We review folders as they come, and will send offers until all positions are filled. Please share with your network 🙏

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Andrew Lampinen @lampinen.bsky.social · 05/01/2026

What can cognitive science learn from AI? In infinitefaculty.substack.com/p/what-cogni... I outline how AI has found that scale and richness of learning experiences fundamentally change learning & generalization — and how I believe we should rethink cognitive experiments & theories in response.

infinitefaculty.substack.com

What cognitive science can learn from AI

#3 in a series on cognitive science and AI

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Navita Goyal @navitagoyal.bsky.social · 02/12/2025

Woah, this is so cool! How was I not aware of this. I just set mine up to prepare for NeurIPS and I am loving it already... it made thousands of accepted paper so much more tractable to navigate

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Hal Daumé III @haldaume3.bsky.social · 21/11/2025

AIM's 2nd round of TTK hiring - building up to 30 - is up! 📅 Ddl 12/22/25 🔬 Accessibility & Learning, plus Sustainability & Social Justice 🧑‍🏫 Associate/Full Prof* 🔗 umd.wd1.myworkdayjobs.com/en-US/UMCP/j... *Assistant-level candidates: apply to departments, mentioning AIM in a cover letter

umd.wd1.myworkdayjobs.com

Senior Tenure Track Faculty at the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM) - Associate Professor/Professor (Open Rank Joint Appointment)

Job Description Summary Organization Summary Statement: The Artificial Intelligence Interdisciplinary Institute at Maryland - AIM (aim.umd.edu) - is hiring 40 faculty over the next several years, incl...

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Najoung Kim @najoung.bsky.social · 19/11/2025

My lab at BU is recruiting PhD students and possibly a postdoc this year! We study humans & machines, centered around topics like meaning, generalization, evaluation methods and design, and the nature of computation and representation that underlie language and cognition. 🫴🫴

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Yanai Elazar @yanai.bsky.social · 13/11/2025

Interested in interpretability, data attribution, evaluation, and similar topics? Interested in doing a postdoc with me? Apply to the prestigious Azrieli program! Link below 👇 DMs are open (email is good too!)

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Alexander Hoyle @alexanderhoyle.bsky.social · 05/11/2025

Happy to be at #EMNLP2025! Please say hello and come see our lovely work

The Medium Is Not the Message: Deconfounding Document Embeddings via Linear Concept Erasure — Tuesday at 11:00, Poster

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification — Tuesday at 14:30, Demo

Measuring Scalar Constructs in Social Science with LLMs — Friday at 10:30, Oral at CSS

How Persuasive is Your Context? — Friday at 14:00, Poster

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Naomi Saphra @nsaphra.bsky.social · 16/10/2025

I am recruiting PhD students to start in 2026! If you are interested in robustness, training dynamics, interpretability for scientific understanding, or the science of LLM analysis you should apply. BU is building a huge LLM analysis/interp group and you’ll be joining at the ground floor.

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Neha Srikanth @nehasrikanth.bsky.social · 29/04/2025

I'll be presenting this work with @rachelrudinger at #NAACL2025 tomorrow (Wednesday 4/30) in Albuquerque during Session C (Oral/Poster 2) at 2pm! 🔬 Decomposing hypotheses in traditional NLI and defeasible NLI helps us measure various forms of consistency of LLMs. Come join us!

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Vishakh Padmakumar @vishakhpk.bsky.social · 29/04/2025

What does it mean for #LLM output to be novel? In work w/ johnchen6.bsky.social, Jane Pan, Valerie Chen and He He, we argue it needs to be both original and high quality. While prompting tricks trade one for the other, better models (scaling/post-training) can shift the novelty frontier 🧵

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Dayeon (Zoey) Ki @dayeonki.bsky.social · 17/04/2025

🚨 New Paper 🚨 1/ We often assume that well-written text is easier to translate ✏️ But can #LLMs automatically rewrite inputs to improve machine translation? 🌍 Here’s what we found 🧵

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Sarah Wiegreffe @sarah-nlp.bsky.social · 03/04/2025

Have work on the actionable impact of interpretability findings? Consider submitting to our Actionable Interpretability workshop at ICML! See below for more info. Website: actionable-interpretability.github.io Deadline: May 9

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Mohit Iyyer @miyyer.bsky.social · 12/03/2025

Thinking about paying $20k/month for a "PhD-level AI agent"? You might want to wait until their web browsing skills are on par with those of human PhD students 😛 Check out our new BEARCUBS benchmark, which shows web agents struggle to perform simple multimodal browsing tasks!

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Nishant Balepur @nbalepur.bsky.social · 11/03/2025

🚨 Our team at UMD is looking for participants to study how #LLM agent plans can help you answer complex questions 💰 $1 per question 🏆 Top-3 fastest + most accurate win $50 ⏳ Questions take ~3 min => $20/hr+ Click here to sign up (please join, reposts appreciated 🙏): preferences.umiacs.umd.edu

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Nishant Balepur @nbalepur.bsky.social · 24/02/2025

🚨 New Position Paper 🚨 Multiple choice evals for LLMs are simple and popular, but we know they are awful 😬 We complain they're full of errors, saturated, and test nothing meaningful, so why do we still use them? 🫠 Here's why MCQA evals are broken, and how to fix them 🧵

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Mohit Iyyer @miyyer.bsky.social · 21/02/2025

How can we generate synthetic data for a task that requires global reasoning over a long context (e.g., verifying claims about a book)? LLMs aren't good at *solving* such tasks, let alone generating data for them. Check out our paper for a compression-based solution!

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Joe Stacey @joestacey.bsky.social · 18/02/2025

This paper is really cool. They decompose NLI (and defeasible NLI) hypotheses into atoms, and then use these atoms to measure the logical consistency of LLMs. E.g. for an entailment NLI example, each hypothesis atom should also be entailed by the premise. Very nice idea 👏👏

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Hal Daumé III @haldaume3.bsky.social · 16/01/2025

Please join us for: AI at Work: Building and Evaluating Trust Presented by our Trustworthy AI in Law & Society (TRIALS) institute. Feb 3-4 Washington DC Open to all! Details and registration at: trails.gwu.edu/trailscon-2025 Sponsorship details at: trails.gwu.edu/media/556

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Hal Daumé III @haldaume3.bsky.social · 09/12/2024

The Impact of Explanations on Fairness in Human-AI Decision-Making: Protected vs Proxy Features Despite hopes that explanations improve fairness, we see that when biases are hidden behind proxy features, explanations may not help. Navita Goyal, Connor Baumler +al IUI’24 hal3.name/docs/daume23... >

meme with three rows.

"this human-ai decision making leads to unfair outcomes" --> "panik"

"let's show explanations to help people be more fair" --> "kalm"

"those explanations are based on proxy features" --> "panik"

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Paola Cascante-Bonilla @pcascanteb.bsky.social · 05/12/2024

This is my first time serving as an AC for a big conference. Just read this great work by Goyal et al. arxiv.org/abs/2411.11437 I'm optimizing for high coverage and low redundancy—assigning reviewers based on relevant topics or affinity scores alone feels off. Seniority and diversity matter!

arxiv.org

Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewing

A large host of scientific journals and conferences solicit peer reviews from multiple reviewers for the same submission, aiming to gather a broader range of perspectives and mitigate individual biase...

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Hal Daumé III @haldaume3.bsky.social · 03/12/2024

Large Language Models Help Humans Verify Truthfulness—Except When They Are Convincingly Wrong Should one use chatbots or web search to fact check? Chatbots help more on avg, but people uncritically accept their suggestions much more often. by Chenglei Si +al NAACL’24 hal3.name/docs/daume24... >

meme with a car veering away from « bad answers from search » to « bad answers from chatbots »

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