3 citations · 6 across the 6 of their papers we have counts for
6 papers
From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors
Jiejun Tan, Zhicheng Dou, Xinyu Yang +4
LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. In local agentic harnesses, an LLM can read and write files, call tools, and reu…
ChatShopBuddy: Towards Reliable Conversational Shopping Agents via Reinforcement Learning
Yiruo Cheng, Kelong Mao, Tianhao Li +3
Conversational shopping agents represent a critical consumer-facing application of Large Language Model (LLM)-powered agents, yet how to effectively apply post-training Reinforceme…
MemSifter: Offloading LLM Memory Retrieval via Outcome-Driven Proxy Reasoning
Jiejun Tan, Zhicheng Dou, Liancheng Zhang +3
As Large Language Models (LLMs) are increasingly used for long-duration tasks, maintaining effective long-term memory has become a critical challenge. Current methods often face a…
CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation
Yiruo Cheng, Kelong Mao, Ziliang Zhao +6
Retrieval-Augmented Generation (RAG) has become a powerful paradigm for enhancing large language models (LLMs) through external knowledge retrieval. Despite its widespread attentio…
A Survey of Conversational Search
Fengran Mo, Kelong Mao, Ziliang Zhao +7
As a cornerstone of modern information access, search engines have become indispensable in everyday life. With the rapid advancements in AI and natural language processing (NLP) te…
Interpreting Conversational Dense Retrieval by Rewriting-Enhanced Inversion of Session Embedding
Yiruo Cheng, Kelong Mao, Zhicheng Dou
Conversational dense retrieval has shown to be effective in conversational search. However, a major limitation of conversational dense retrieval is their lack of interpretability,…