7 papers
CARE: Pre-Execution Command Verification for Shell-Executing LLM Agents
Wenxiao Zhang, Yu Liu, Zhiwei Yang +7
Large Language Model (LLM) agents are increasingly used for coding and terminal automation, making shell-command dispatch a high-stakes runtime control point. We study command-leve…
When the Same Musical Knowledge Forgets Differently: A Clean Probe of Pathway-Dependent Forgetting
Yu Liu, Zhiwei Yang, Wenxiao Zhang +8
A model can learn that the piano piece Für Elise is calm and reflective by listening to the audio or by reading a text description, but does it matter which route that knowledge t…
Trans-RAG: Query-Centric Vector Transformation for Secure Cross-Organizational Retrieval
Yu Liu, Kun Peng, Wenxiao Zhang +4
Retrieval Augmented Generation (RAG) systems deployed across organizational boundaries face fundamental tensions between security, accuracy, and efficiency. Current encryption meth…
STIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction System
Wenxiao Zhang, Yu Liu, Qiang sun +5
Extracting structured knowledge from unstructured data still faces practical limitations: entity and event extraction pipelines remain brittle, knowledge graph construction require…
Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning
Yu Liu, Wenxiao Zhang, Diandian Guo +6
Retrieval-augmented generation (RAG) can achieve strong answer accuracy on multi-hop questions, but outcome-level rewards often leave reasoning traces weakly grounded and difficult…
PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop Question Answering
Yu Liu, Wenxiao Zhang, Cong Cao +10
Answering real-world open-domain multi-hop questions over massive corpora is a critical challenge in Retrieval-Augmented Generation (RAG) systems. Recent research employs reinforce…