5 papers
Textual Belief States for World Models: Identifiable Representation Learning Under Strict Mediation
Xiang Gao, Kaiwen Dong, Yuguang Yao +2
World models in partially observed environments rely on latent representations that summarize interaction history, but in many modern LLM-based architectures predictive performance…
Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval
Padmaja Jonnalagedda, Yuguang Yao, Xiang Gao +2
Real-world data spans tables, documents, and semi-structured files with implicit semantics. Querying this data requires integrating evidence across inconsistent schemas and formats…
AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
Yiheng Shu, Bernal Jiménez Gutiérrez, Saisri Padmaja Jonnalagedda +3
Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes. Continual learning…
ToolPRMBench: Evaluating and Advancing Process Reward Models for Tool-using Agents
Dawei Li, Yuguang Yao, Zhen Tan +2
Reward-guided search methods have demonstrated strong potential in enhancing tool-using agents by effectively guiding sampling and exploration over complex action spaces. As a core…
RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning
Xiang Gao, Yuguang Yao, Qi Zhang +5
Large language models (LLMs) often struggle to use tools reliably in domain-specific settings, where APIs may be idiosyncratic, under-documented, or tailored to private workflows.…