Yuling Gu

First year of PhD-ing at NYU in NYC 🚕🍎 | Previously @nyuniversity ➡️ @UW ➡️ @allen_ai @[email protected]

[Yuling Gu @gu_yuling]

🎉 SimpleToM has been accepted to #ICLR2026!

LLMs can tell you what someone knows (explicit ToM).
But when asked to apply it to predict behavior or judge actions (applied ToM), even frontier LLMs still fail. 🤯

The gap between knowing and applying is real… and huge. 👀

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[Yuling Gu @gu_yuling]

I can’t be there in person due to visa issues, but please meet my amazing co-authors! My DM (and email) are open if you’d like to connect!

[Yuling Gu @gu_yuling]

Check out SimpleToM at #ICLR2026 where we reveal a critical fragility in LLMs’ social reasoning — the explicit vs. applied ToM gap.

🗓️Fri, Apr 24, 2026 3:15 PM – 5:45 PM BRT
📍Pavilion 3 P3-#1407

[Yuling Gu @gu_yuling]

🎉 SimpleToM has been accepted to #ICLR2026!

LLMs can tell you what someone knows (explicit ToM).
But when asked to apply it to predict behavior or judge actions (applied ToM), even frontier LLMs still fail. 🤯

The gap between knowing and applying is real… and huge. 👀

1/

[Yuling Gu @gu_yuling]

Work done during my time at @allen_ai with wonderful collaborators Oyvind Tafjord, @hyunw_kim, @jaredlcm, @Ronan_LeBras, Peter Clark, @YejinChoinka.

📜 Paper: https://t.co/Lv13te4Idy
💻 Code: https://t.co/FpzRETe1kD

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[Yuling Gu @gu_yuling]

🎉 SimpleToM has been accepted to #ICLR2026!

LLMs can tell you what someone knows (explicit ToM).
But when asked to apply it to predict behavior or judge actions (applied ToM), even frontier LLMs still fail. 🤯

The gap between knowing and applying is real… and huge. 👀

1/

[Yuling Gu @gu_yuling]

SimpleToM exposes this gap 🔎 and provides a benchmark to diagnose, improve, and push LLMs toward robust social reasoning 🚀

Try SimpleToM on any model : https://t.co/FnGe9Oa9wk

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[Kyunghyun Cho @kchonyc]

i gave a keynote talk at NeurIPS'25 just last week. here's the slide deck (link below) i've used to share my thoughts on who we are and what we do.

[Yuling Gu @gu_yuling]

Super proud of the amazing work that my Ai2 friends have been doing! 🤩 Check this out! ✨

[Ai2 @allen_ai]

Announcing Olmo 3, a leading fully open LM suite built for reasoning, chat, & tool use, and an open model flow—not just the final weights, but the entire training journey.
Best fully open 32B reasoning model & best 32B base model. 🧵

[Yuling Gu @gu_yuling]

@soldni @kylelostat @allen_ai Looks cool 🤩 Is this bag the latest swag? 👀

[Danica Dillion @danicajdillion]

🌍 Introducing WorldValuesBench!

A benchmark to evaluate how well LLMs reflect cultural differences in human values.

Built from 94k+ participants in the World Values Survey → 20M examples of (demographics, value question → answer).

🧵

[David Heineman @davidheinnman]

Evaluating language models is tricky, how do we know if our results are real, or due to random chance?

We find an answer with two simple metrics: signal, a benchmark’s ability to separate models, and noise, a benchmark’s random variability between training steps 🧵

[Yuling Gu @gu_yuling]

@code_star Super excited to have more people like you joining in, looking into the details behind evals, and asking these interesting + important questions! 👍

[Yuling Gu @gu_yuling]

Come to our poster session on Friday, May 2, 9-10.30 am (Hall 3) to chat more!

[Yuling Gu @gu_yuling]

Excited to be at #NAACL2025 in Albuquerque this week! I'll be presenting "OLMES: A Standard for Language Model Evaluations" (https://t.co/SmjBV2Szsk)! Work done with my wonderful collaborators at @allen_ai ❤️

[Yuling Gu @gu_yuling]

This effort toward an open language model evaluation standard doesn’t just end here. Since the submission of our NAACL paper, we have added more tasks to OLMES, including generative and reasoning tasks, all openly available in our repository (https://t.co/54sbLDWWBM).

[Ai2 @allen_ai]

Imagine AI doing science: reading papers, generating ideas, designing and running experiments, analyzing results… How many more discoveries can we reveal? 🧐

Meet CodeScientist, a promising next step toward autonomous scientific discovery. 🧵

[Kyle Lo @kylelostat]

kicking off 2025 with our OLMo 2 tech report while payin homage to the sequelest of sequels 🫡

🚗 2 OLMo 2 Furious 🔥 is everythin we learned since OLMo 1, with deep dives into:

🚖 stable pretrain
🚔 lr anneal 🤝 data curricula 🤝 soups
🚘 tulu post-train
🚜 compute infra

👇🧵