activity
20242026
most citedDocs2KG: Unified Knowledge Graph Construction from Heterogeneous Documents Assisted by Large Language Models

4 citations · 6 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CL2026

ClueWeaver: Reward-Guided Dual-Agent Evidence Reasoning for Compact LLMs on Literary Long Narratives

Jihao Zhu, Zhiwei Yang, Wenxiao Zhang +7

Humanities and social science research requires close reading of long narrative materials such as novels, scripts, archives, and case reports, yet many users have limited access to…

cs.CR2026

CARE: Pre-Execution Command Verification for Shell-Executing LLM Agents

Yu Liu, Wenxiao Zhang, 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…

cs.SD2026

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 to…

cs.CR2026

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…

cs.DB2026

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…

cs.CL2026

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…