5 papers
The yes-no bias of large language models reflects answer order and wording, not shifts in moral judgment
Haonan Huang
Large language models (LLMs) increasingly issue judgments read as binary verdicts, and a growing literature reports such judgments shifting under logically irrelevant changes of wo…
Grounded autonomous research: a fault-tolerant LLM pipeline from corpus to manuscript in frontier computational physics
Haonan Huang
Autonomous-research agents have demonstrated end-to-end LLM automation in machine-learning sandboxes where execution provides calibration. Frontier physical science differs categor…
Grounded autonomous scrutiny at scale: emergent critique from reproduction of published computational physics papers
Haonan Huang
Autonomous LLM agents now produce complete research artifacts in machine-learning sandboxes, but real computational physics is harder: experiments are first-principles calculations…
From Experiments to Expertise: Scientific Knowledge Consolidation for AI-Driven Computational Physics
Haonan Huang
While large language models (LLMs) have transformed AI agents into proficient executors of computational materials science, performing a hundred simulations does not make a researc…
RPS: Information Elicitation with Reinforcement Prompt Selection
Tao Wang, Jingyao Lu, Xibo Wang +5
Large language models (LLMs) have shown remarkable capabilities in dialogue generation and reasoning, yet their effectiveness in eliciting user-known but concealed information in o…