activity
20242026
collaborators

12 papers

cs.CL2026

Verbalizable Representations Form a Global Workspace in Language Models

Wes Gurnee, Nicholas Sofroniew, Adam Pearce +13

Out of everything the human brain processes, only a small fraction is consciously accessible, in the sense of being available for verbal report, deliberate control, and flexible re…

cs.CL2026

LLMs Can Get "Brain Rot": A Pilot Study on Twitter/X

Shuo Xing, Junyuan Hong, Yifan Wang +5

We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language models (LLMs). To unveil junk effects, we…

cs.CV2026

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

Zhiwen Fan, Jian Zhang, Renjie Li +15

The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes, aiming for human-like visual-spatial…

cs.AI2026

Emotion Concepts and their Function in a Large Language Model

Nicholas Sofroniew, Isaac Kauvar, William Saunders +13

Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore implications for alignment-releva…

cs.AI2026

Neurosymbolic LoRA: Why and When to Tune Weights vs. Rewrite Prompts

Kevin Wang, Neel P. Bhatt, Cong Liu +7

Large language models (LLMs) can be adapted either through numerical updates that alter model parameters or symbolic manipulations that work on discrete prompts or logical constrai…

cs.CL2025

SEAL: Steerable Reasoning Calibration of Large Language Models for Free

Runjin Chen, Zhenyu Zhang, Junyuan Hong +2

Large Language Models (LLMs), such as OpenAI's o1-series have demonstrated compelling capabilities for complex reasoning tasks via the extended chain-of-thought (CoT) reasoning mec…