8 papers
ForestBench: A Unified Graph Framework for Evaluating Multi-Agent Collaboration
Guo Chen, Ziwen Li, Reed Li +4
Multi-agent systems (MAS) built on Large Language Models (LLMs) are proliferating rapidly, but their heterogeneous execution traces provide no common basis for evaluation across me…
NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation
Guo Chen, Ziwen Li, Maolin Zheng +3
The paper proposes NGM-RAG, a framework that combines graph neural networks with text matching to improve retrieval-augmented generation for tasks requiring multi-hop reasoning and…
RAGPPI: RAG Benchmark for Protein-Protein Interactions in Drug Discovery
Youngseung Jeon, Ziwen Li, Thomas Li +3
Retrieving the biological impacts of protein-protein interactions (PPIs) is essential for target identification (Target ID) in drug development. Given the vast number of proteins i…
LLM Anonymization Against Agentic Re-Identification
Ziwen Li, Jianing Wen, Tianshi Li
Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-identification, yet those same deta…
Disclose with Care: Designing Privacy Controls in Interview Chatbots
Ziwen Li, Ziang Xiao, Tianshi Li
Collecting data on sensitive topics remains challenging in HCI, as participants often withhold information due to privacy concerns and social desirability bias. While chatbots' per…
Supporting Medicinal Chemists in Iterative Hypothesis Generation for Drug Target Identification
Youngseung Jeon, Christopher Hwang, Ziwen Li +6
While drug discovery is vital for human health, the process remains inefficient. Medicinal chemists must navigate a vast protein space to identify target proteins that meet three c…