2 citations · 2 across the 11 of their papers we have counts for
6 papers · 1 filter
Output Discipline Sets the Floor: A Falsification-Guided, Model-Agnostic Agent Protocol for Auditable Hypothesis-Driven Decision Making
Jing Liu, Yongxing Qi, Ping Yao +1
What binds large language models on auditable, hypothesis-driven decision tasks, where every candidate can be checked against the evidence? On the public TCMEval-SDT benchmark for…
From Association to Causation: Improving Retrieval Precision of Retrieval-Augmented Generation via Causal Relations and an Attention Mechanism
Jing Liu, Yongxing Qi, Muchen Jiang +7
Retrieval-Augmented Generation (RAG) grounds LLM generation on retrieved documents, but the standard terminal retrieval stage--dense-vector similarity, optionally followed by reran…
Cookie-Bench: Continuous On-screen Key Interaction Evaluation for Web Generation
Haoyue Yang, Zhangxiao Shen, Fan Ding +8
Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed remains costly because human…
LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws
Xu Ouyang, Deyi Liu, Yuhang Cai +5
Existing scaling laws for Large Language Models (LLMs), predominantly monotonic power laws, fail to explain emerging non-monotonic phenomena such as catastrophic overtraining and q…
Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
Ruiyang Ren, Yuhao Wang, Yunsen Liang +8
Clinical diagnosis is a complex cognitive process, grounded in dynamic cue acquisition and continuous expertise accumulation. Yet most current artificial intelligence (AI) systems…
FormalEvolve: Neuro-Symbolic Evolutionary Search for Diverse Autoformalization
Haijian Lu, Wei Wang, Jing Liu
Autoformalization aims to produce formal statements that compile and faithfully preserve the intended meaning of informal mathematics. Yet standard single-output evaluation collaps…