We’re excited about Oolong as a challenging benchmark for information aggregation! Let us know which models we should benchmark next 👀 Paper: arxiv.org/abs/2511.02817 Dataset: huggingface.co/oolongbench Code: github.com/abertsch72/o... Leaderboard: oolongbench.github.io

Can LLMs accurately aggregate information over long, information-dense texts? Not yet… We introduce Oolong, a dataset of simple-to-verify information aggregation questions over long inputs. No model achieves >50% accuracy at 128K on Oolong!

Yes! tbh this method is probably much more immediately useful for helping one understand subtle differences between [models trained on] subtly different data subsets, vs a loftier goal of helping one find "the" best data mixture -- to anyone considering this method, please feel free to reach out :)

Come through! #492 in Hall 2!, 10am-12:30pm

Our paper documenting the environmental impacts of creating OLMo language models is the most honest and comprehensive characterization I know of, including training, development (!) and inference costs. If you're at ICLR chat with @jacobcares.bsky.social & @clarana.bsky.social Sat morning 10-12:30!

📜Paper: arxiv.org/abs/2503.05804 ✍️Thanks to my illustrious coauthors @clarana.bsky.social @jaredfern.bsky.social timdettmers.com @strubell.bsky.social @jessedodge.bsky.social, t'was a fun project 🌏

I'm in Singapore for @iclr-conf.bsky.social ! Come check out our spotlight paper on the environmental impact of training OLMo (link in next tweet) during the Saturday morning poster session from 10-12:30 -- happy to chat about this or anything else! DMs should be open, email works too

We've received multiple notes that NOAA research services (Office of Oceanic and Atmospheric Research) may go offline at midnight. @safeguardingdata.bsky.social is working on web archiving, but if others want to nominate on this, that might be good: digital2.library.unt.edu/nomination/G...

How can we better think and talk about human-like qualities attributed to language technologies like LLMs? In our #CHI2025 paper, we taxonomize how text outputs from cases of user interactions with language technologies can contribute to anthropomorphism. arxiv.org/abs/2502.09870 1/n

Did you know? Gestures used to express universal concepts—like wishing for luck—vary DRAMATICALLY across cultures? 🤞means luck in US but deeply offensive in Vietnam 🚨 📣 We introduce MC-SIGNS, a test bed to evaluate how LLMs/VLMs/T2I handle such nonverbal behavior! 📜: arxiv.org/abs/2502.17710

the science of LMs should be fully open✨ today @akshitab.bsky.social @natolambert.bsky.social and I are giving our #neurips2024 tutorial on language model development. everything from data, training, adaptation. published or not, no secrets 🫡 tues, 12/10, 9:30am PT ☕️ neurips.cc/virtual/2024...

How open is “open” AI, really? It isn’t just about making models reusable. If the origin of data is opaque, if labor is hidden & exploited, if frameworks are dominated by Big Tech, if computational power is mastered by an oligopoly…‘open’ is just a label. Meredith Whittaker & friends in Nature.

I noticed a lot of starter packs skewed towards faculty/industry, so I made one of just NLP & ML students: go.bsky.app/vju2ux Students do different research, go on the job market, and recruit other students. Ping me and I'll add you!

💬 Have you or a loved one compared LM probabilities to human linguistic acceptability judgments? You may be overcompensating for the effect of frequency and length! 🌟 In our new paper, we rethink how we should be controlling for these factors 🧵:

@jaredfern.bsky.social is at 162

Hi I am at 232 in the back of the riverfront room!

I'm at EMNLP! Presenting the poster for this paper on Thursday morning (10:30-12), Session F Riverfront Hall, come say hi :)

(Hehe first bsky post!) I'll be at #EMNLP2024 💃🌴! Happy to chat about (among other things): ✨linguistically+cognitively motivated evaluation ✨NLP for low-resource+endangered languages ✨figuring out what features of language data LMs are *actually* learning I'll be presenting two posters 🧵:

scrolling,,, minimal doom ?!

Understanding “Democratization” in NLP and ML Research - joint work @arjunsubgraph.bsky.social and I co-led with Dietrich Klakow and @zeerak.bsky.social aclanthology.org/2024.emnlp-m...

A starter pack for #NLP #NLProc researchers! 🎉 go.bsky.app/SngwGeS

Building/customizing your own LLM? You'll want to curate training data for it, but how do you know what makes the data good? You can try out recipes👩‍🍳 iterate on ✨vibes✨ but we can't actually test all possible combos of tweaks,,, right?? 🙅‍♂️WRONG! arxiv.org/abs/2410.15661 (1/n) 🧵

I think it’s fucked up that EMNLP 2023 emailed Findings authors on Nov 8 that they *might* have a chance to present at main conf, but also don’t forget to early register by Nov 12. Then only let authors know of *virtual* poster assignment 10 min before early registration closed.

Not at all surprised to see that junior people support the proposed anonymity changes to the ACL policies. Speaking for myself and my "early career" goals, the anonymity deadlines are incredibly stressful and (as far as I can tell) not beneficial to me.

By learning our history, rather than exceptionalizing the current moment, it's easy to discover worthwhile directions for researchers interested in contributing to language model capabilities without access to industry-scale training. Enjoy your research!

Daylight Saving Time is increasingly hard to notice when my digital devices are like, "What? Nothing happened. We know what time it is." And my stove is left blinking and screaming, "IT HAPPENED! TIME SHIFTED UNNATURALLY! THEY'RE ALL LYING! ONLY I KNOW! ONLY I REMEMBER!"

Hey I just met you I'm off to hunt whale but here's my novel so call me Ishmael

incredible coinage

Ok I finally read rabbit test now that it has a Hugo and this story is So Good www.uncannymagazine.com/article/rabb...

Really excited about this one and had such a blast working with @siree.sh @abertsch.bsky.social @davidthewid.bsky.social @strubell.bsky.social! Please read our paper and reach out with any questions, we'd love to chat! See y'all in Singapore :)

We all know that “recently large language models have”, “large language models are”, and “large language models can.” But *why* LLMs? How did we get here? (where is “here”?) What forces are shaping NLP, and how recent are they, actually? To appear at EMNLP 2023: arxiv.org/abs/2310.07715

🚨 new paper 🚨 Can we train for flat minima with less catastrophic OOD forgetting? 

We propose Trust Region Aware Minimization for smoothness in parameters+representations. TL;DR representations matter just as much! arxiv.org/abs/2310.03646 w/ @nsaphra.bsky.social Pradeep Dasigi + Hao Peng