From the 1 of 27 linked papers with an AI index.
27 papers
Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery
Taolin Han, Yuchen Zhang, Jinghang Wang +22
Large language models (LLMs) are increasingly involved in scientific discovery, yet it remains unclear whether they can support complex real laboratory science. Here we introduce S…
Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks
Xuan Ren, Weiqi Zhai, Tianle Pu +3
Scientific reasoning benchmarks typically evaluate large language models (LLMs) using final-answer accuracy. However, a correct answer does not necessarily demonstrate the reasonin…
Living-Harness Is an Interactive-Agent Evolver
Yuetian Du, Yucheng Wang, He Xu +9
The paper introduces Living-Harness, a self‑evolving harness for large language model agents that updates procedural knowledge from episode feedback, enabling the agent to avoid re…
Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements
Xinke Tong, Xuanming Zhang, Tianyi Tang +10
Do Large Language Models (LLMs) possess genuine structural reasoning, or merely rely on surface-level pattern matching? The financial domain, demanding numerical precision and mult…
Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery
Tianyun Zhong, Wangyi Jiang, Wei Wang +15
Large language models (LLMs) excel at answering pre-specified questions, yet their ability to navigate the open-ended, pre-conclusion stage of discovery remains largely unmeasured.…
LA4VLA: Learning to Act without Seeing via Language-Action Pretraining
Tao Lin, Yuxin Du, Yiran Mao +13
Vision-Language-Action (VLA) models are commonly pretrained on robot demonstrations by jointly mapping visual observations and language instructions to actions. However, dense visu…