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cs.AI2025
Reducing Belief Deviation in Reinforcement Learning for Active Reasoning
Deyu Zou, Yongqiang Chen, Jianxiang Wang +5
Active reasoning requires large language model (LLM) agents to interact with external sources and strategically gather information to solve problems in multiple turns. Central to t…
cs.CR2025
Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark
Xinjie Shen, Mufei Li, Pan Li
The deployment of Large Language Models (LLMs) in embodied agents creates an urgent need to measure their privacy awareness in the physical world. Existing evaluation methods, howe…
cs.CL2025
Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation
Deyu Zou, Yongqiang Chen, Mufei Li +5
Graph-based retrieval-augmented generation (RAG) enables large language models (LLMs) to ground responses with structured external knowledge from up-to-date knowledge graphs (KGs)…