15 citations · 16 across the 5 of their papers we have counts for
8 papers
ConMem: Counterfactual Multi-Scenario Probing for Resolving LLM Memory Misalignment
Shuning Zhang, Tenghao Ji, Jingruo Chen +3
Long-term memory is critical for autonomous Large Language Model (LLM) agents executing multi-session, long-horizon tasks. However, existing memories often inappropriately store, r…
What should AI forget? A design and taxonomy for negative space governance in AI memory
Eryue Xu, Ke Ding, Ting-Yu Chang +2
AI memory personalizes assistants, yet users want some disclosed information forgotten. We characterize the negative space of AI memory, where protection should take precedence ove…
Characterizing Memory Misalignment in Human-LLM Interaction From User Perspectives
Jingruo Chen, Shuning Zhang, Eryue Xu +2
While memory enhances personalization in LLM-based conversational agents, it suffers from memory misalignment, where memories violate user expectations. We present a mixed-methods…
CIDER: A Dataset of Contextual Disclosure Boundaries for Privacy Preference Alignment
Bingcan Guo, Eryue Xu, Jijie Zhou +2
Aligning large language models (LLMs) with human privacy preferences requires capturing individuals' disclosure boundaries beyond general privacy norms. However, a gap remains in e…
Comparing Human Oversight Strategies for Computer-Use Agents
Chaoran Chen, Zhiping Zhang, Zeya Chen +9
LLM-powered computer-use agents (CUAs) shift users from direct manipulation to supervising an unfolding action sequence, yet existing oversight research mostly evaluates static dec…
From Fragmentation to Integration: Exploring the Design Space of AI Agents for Human-as-the-Unit Privacy Management
Eryue Xu, Tianshi Li
Managing one's digital footprint is overwhelming, as it spans multiple platforms and involves countless context-dependent decisions. Recent advances in agentic AI offer ways forwar…
It's My Agent, Not Me: Personal Privacy Boundaries in AI-Delegated Information Sharing
Bingcan Guo, Eryue Xu, Zhiping Zhang +1
Aligning AI systems with human privacy preferences requires understanding individuals' nuanced disclosure behaviors beyond general privacy norms. Yet eliciting these boundaries rem…
Rescriber: Smaller-LLM-Powered User-Led Data Minimization for LLM-Based Chatbots
Jijie Zhou, Eryue Xu, Yaoyao Wu +1
The proliferation of LLM-based conversational agents has resulted in excessive disclosure of identifiable or sensitive information. However, existing technologies fail to offer per…