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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…