3 papers
cs.CL2026
Do VLMs Align Better with Humans than LLMs during Natural Reading?
Jinzhou Wu, Zhengwu Ma, Jixing Li +2
Large language models have become increasingly useful computational models of human language processing, but it remains open whether vision-language learning makes text representat…
cs.CL2026
ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection
Changjiang Gao, Zixian Huang, Kaichen Yang +3
Current large reasoning models (LRMs) have shown strong ability on challenging tasks after reinforcement learning (RL) based post-training. However, previous work mainly focuses on…
q-bio.NC2025
Brains and language models converge on a shared conceptual space across different languages
Zaid Zada, Samuel A Nastase, Jixing Li +1
Human languages differ widely in their forms, each having distinct sounds, scripts, and syntax. Yet, they can all convey similar meaning. Do different languages converge on a share…