Linyang He

Hearing aids amplify all incoming sound, and so struggle with noisy surroundings. Brain-controlled hearing tech from @NimaMesgarani, @infinivishal & team could lead to a new generation of hearing systems that help people single out a voice in a crowd. Read more: zuckermaninstitute.columbia.edu/brain-controll…

🚀 Announcing the Chinese BabyLM Challenge: the first shared task on data-efficient pretraining for Chinese. 📍 Co-located with NLPCC 2026 (Nov 3–5, Macau🇨🇳🇲🇴) Can you train a strong Chinese LM on just ~100M words? chinese-babylm.github.io 🧵 👇(1/6)

1/7 How can we develop decoding methods that generalize to novel subjects without any fine-tuning? Excited to share our recent collaboration to appear at CVPR 2026! Work led by Andrew Luo's group, with many collaborators (@_jacobprince_ , Mike Tarr, @KriegeskorteLab and others). code: github.com/ezacngm/brainC… paper: arxiv.org/abs/2604.08537

I think we finally made really significant progress on the biggest unsolved "developmental AI" problem: learning from human-scale data. Key idea: zero-shot world models that support concept extraction via approximate causal inference. amazing collab w/ @khai_loong_aw @mcxfrank

Between theorem recognition and theorem proving lies theorem understanding. We introduce LiveMathematicianBench: a live, contamination-resistant testbed for research-level mathematical reasoning, built from post-cutoff arXiv theorems. It probes a capability that existing benchmarks rarely isolate: whether models can understand theorem statements, track delicate assumptions, reason over logical structure, and leverage proof-level guidance. livemathematicianbench.github.io

@hendrydong xianmu work anywhere

Burned some after-work hours spinning Copilot CLI into WeChat. Full multi-session support. WeChat ←→ copilot-wechat ←→ Copilot CLI (ACP) ←→ GPT / Claude / Gemini That makes me work anywhere with my phone. We're moving past static apps. The new meta is Dynamic Personal Interfaces. Spin up a bespoke workspace in minutes, throw it into your favorite chat app, and ship from anywhere. New vibes are incoming! github.com/hendrydong/cop…

SFT curates responses. RL curates sampling.   RL improves by curating what the model experiences: condition; distribution; weighting of what gets learned from.   Better signal curation shifts the performance-compute curve upward.   Full write-up below 👇 hendrydong.github.io/blogs/pages/rl…

#VideoReason We are open-sourcing the entire VBVR stack to speed-up the arrival of video reasoning as the next fundamental paradigm of intelligence - 150+ synthetic generators - 1 million training clips - Cloud-scale data factory - Unified EvalKit - 100 rule-based evaluators - Strong baseline model Checkout at video-reason.com

[1/n]🧠Can LLMs understand viral meme clips like Rickrolling, Leekspin, Nyan Cat, and “愛♡スクリ～ム”? 🎉Happy to share AVMeme Exam, the funniest audio/video understanding benchmark ever! We eval multimodal LLMs on the meme clips you hear & see daily on YouTube, TikTok &Bilibili

Our paper is accepted to ICLR 2026! 🎉 Code & models released: github.com/Yikai-Wang/nvg

@kanishkamisra @unireps Wow thank you Kanishka! Your earlier work made this possible😃

@LinyangNeuroAI presenting a classifier free representational analyses on BLIMP and COMPS @unireps — enjoying how creatively he’s been using (and extending) minimal pair datasets!

Many thanks to my amazing co-authors: Tianjun Zhong, @NeuroRJ, Gavin Mischler, Prof. @micahgoldblum and my advisor Prof. @NimaMesgarani! #NeuroAI #LLM #NeurIPS2025 #NeurIPS #reasoning

5️⃣ Takeaway: - Raw LLM embeddings = biased toward shallow linguistic features. - Residual disentanglement exposes the deeper, reasoning-specific representations shared by brains and models.

🧠New at #neurips2025! TL;DR: We introduce the first "reasoning embedding" and uncover its unique spatio-temporal pattern in the brain. 🔗arxiv.org/abs/2510.228...