11 papers
Equitable System-Prompt Selection via Constrained Mixed-Strategy GroupDRO
Mengyu Xu, Qiaoxin Yang, Zhihan Liu +4
Large language models are increasingly used for information seeking, yet semantically equivalent questions phrased in different ways can receive answers of considerably different q…
The Text Uncanny Valley: Non-Monotonic Performance Degradation in LLM Information Retrieval
Zekai Tong, Ruiyao Xu, Aryan Shrivastava +2
Existing Large Language Model (LLM) benchmarks primarily focus on syntactically correct inputs, leaving a significant gap in evaluation on imperfect text. In this work, we study ho…
Geometry-Calibrated Conformal Abstention for Language Models
Rui Xu, Yi Chen, Sihong Xie +1
When language models lack relevant knowledge for a given query, they frequently generate plausible responses that can be hallucinations, rather than admitting being agnostic about…
Cat-DPO: Category-Adaptive Safety Alignment
Tiankai Yang, Yi Nian, Xinyuan Li +6
Aligning large language models with human preferences must balance two competing goals: responding helpfully to legitimate requests and reliably refusing harmful ones. Most prefere…
CoAct: Co-Active LLM Preference Learning with Human-AI Synergy
Ruiyao Xu, Mihir Parmar, Tiankai Yang +3
Learning from preference-based feedback has become an effective approach for aligning LLMs across diverse tasks. However, high-quality human-annotated preference data remains expen…
No Attacker Needed: Unintentional Cross-User Contamination in Shared-State LLM Agents
Tiankai Yang, Jiate Li, Yi Nian +5
LLM-based agents increasingly operate across repeated sessions, maintaining task states to ensure continuity. In many deployments, a single agent serves multiple users within a tea…