3 citations · 7 across the 36 of their papers we have counts for
9 papers · 1 filter
OpenHalDet: A Unified Benchmark for Hallucination Detection across Diverse Generation Scenarios
Xinyi Li, Zhen Fang, Yongxin Deng +12
Hallucination detection is essential for the reliable deployment of large language models (LLMs). However, existing evaluations face two core challenges: inconsistent inference con…
DECOR: Auditing LLM Deception via Information Manipulation Theory
Linyue Cai, Samuel Yeh, Jwala Dhamala +2
Large language models can deceive by subtly manipulating truthful information -- omitting key facts, shifting focus, or obscuring meaning -- making such behavior difficult to detec…
Auditing Agent Harness Safety
Chengzhi Liu, Yichen Guo, Yepeng Liu +8
LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. However, a harness can return a c…
On Safety Risks in Experience-Driven Self-Evolving Agents
Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8
Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…
How Retrieved Context Shapes Internal Representations in RAG
Samuel Yeh, Sharon Li
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by conditioning generation on retrieved external documents, but the effect of retrieved context is often…
Thinking Is Not Telling: Information Disclosure in User-Service LLM Agents
Jiatong Li, Changdae Oh, Hyeong Kyu Choi +2
User-engaged LLM agents increasingly operate in service scenarios where task success depends on coordination between the agent, the user, and a stateful environment. In such intera…