activity
20242026
collaborators

23 papers

cs.CR2026

Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents

Puji Wang, Yingchen Zhang, Ruqing Zhang +2

Persistent AI agents extend large language models (LLMs) beyond single-turn interaction into long-lived software systems. Unlike traditional chat assistants, unsafe content in thes…

cs.IR2026

Querit-Reranker: Training Compact Multilingual Rerankers via Efficient Label-Free Distribution Adaptation

Yunfei Zhong, Jun Yang, Wei Huang +7

Deployable multilingual rerankers must generalize across languages, domains, and target ranking tasks while remaining efficient enough for second-stage reranking. However, adapting…

cs.IR2026

AdversarialCoT: Single-Document Retrieval Poisoning for LLM Reasoning

Hongru Song, Yu-An Liu, Ruqing Zhang +4

Retrieval-augmented generation (RAG) enhances large language model (LLM) reasoning by retrieving external documents, but also opens up new attack surfaces. We study knowledge-base…

cs.IR2026

Reason to Retrieve: Enhancing Query Understanding through Decomposition and Interpretation

Yunfei Zhong, Jun Yang, Yixing Fan +4

Query understanding (QU) aims to accurately infer user intent to improve document retrieval. It plays a vital role in modern search engines. While large language models (LLMs) have…

cs.CL2025

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning

Wenda Wei, Yu-An Liu, Ruqing Zhang +6

Retrieval-augmented generation (RAG) has proven to be effective in mitigating hallucinations in large language models, yet its effectiveness remains limited in complex, multi-step…

cs.IR2025

Does Generative Retrieval Overcome the Limitations of Dense Retrieval?

Yingchen Zhang, Ruqing Zhang, Jiafeng Guo +3

Generative retrieval (GR) has emerged as a new paradigm in neural information retrieval, offering an alternative to dense retrieval (DR) by directly generating identifiers of relev…