8 papers
FGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization
Hao Chen, Ziyang Ling, Ronald X. Xu +1
Large language model (LLM)-guided Bayesian optimization (BO) uses past observations to guide search, but proposed directions and their revision can remain implicit. We propose Feed…
CAST: History-Adaptive Spectral Clipping for LLM Pretraining
Jiacheng Li, Jianchao Tan, Kefeng Zhang +2
Soft spectral clipping (SSC) reduces gradient singular values, but its effect depends on the gradient scale and clipping threshold. We introduce CAST (Clipping with Adaptive Scales…
TimeRSI: Towards Self-Improved Agentic Deployment for Time-Series Foundation Models
Haoxin Liu, Deqing Fu, Lucheng Fu +4
Time-series foundation models provide strong zero-shot forecast, but deployment for real-world applications still requires task-specific designs for model inputs and outputs. Direc…
BioPRM: Step-Level Consistency Verification of Biological Protocols
Bowen Shao, Ziyang Ling, Ronald Xu +1
Process reward models (PRMs) provide fine-grained supervision for assessing intermediate steps in language-model outputs, but their application to biological protocols presents dis…
From Hindsight to Foresight: Dissecting Clinical Evidence Acquisition in Large Language Models
Ziyang Ling
Large language models (LLMs) often diagnose full sight, static clinical cases well yet struggle in foresight, dynamic diagnosis. Prior work has improved this limitation by quantify…
Training-Free BioNEL-RAG: Advancing Biomedical Entity Linking through Retrieval-Augmented Generation and Large Language Model
Ziyi Chen, Hui Liu, Ziyang Ling +2
Biomedical Named Entity Linking (BioNEL) is the task of mapping mentions extracted from biomedical texts to canonical entities or concepts in the standardized knowledge base. Altho…