17 papers
SurgVLA-Bench: Towards Evaluating Vision-Language-Action Models for Laparoscopic Surgical Robotics
Jiashuo Sun, Yue He, Wenxuan Liu +4
Vision-Language-Action (VLA) models represent a promising direction for embodied intelligence in surgical robotics. Despite the prevalence of VLA benchmarks for general robotics, s…
Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses
Pengcheng Jiang, Zhiyi Shi, Kelly Hong +5
Search agents are often trained as policies over growing transcripts: the model must decide how to search while also remembering what it has seen, which evidence is useful, which c…
Learning to Predict Future-Aligned Research Proposals with Language Models
Heng Wang, Pengcheng Jiang, Jiashuo Sun +4
Large language models (LLMs) are increasingly used to assist ideation in research, but evaluating the quality of LLM-generated research proposals remains difficult: novelty and sou…
Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation
Jiashuo Sun, Jimeng Shi, Yixuan Xie +10
Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on multi-hop questions, where so…
Let the Abyss Stare Back Adaptive Falsification for Autonomous Scientific Discovery
Peiran Li, Fangzhou Lin, Shuo Xing +5
Autonomous scientific discovery is entering a more dangerous regime: once the evaluator is frozen, a sufficiently strong search process can learn to win the exam without learning t…
TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation
Jiashuo Sun, Yixuan Xie, Jimeng Shi +2
Retrieval-Augmented Generation (RAG) helps large language models (LLMs) answer knowledge-intensive and time-sensitive questions by conditioning generation on external evidence. How…