activity
20242026
most citedAlignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

MicroVerse: An Instrument for Measuring Self-Authored Identity Drift in Long-Horizon Multi-Agent Language-Model Simulations

Sky Ng, Brihi Joshi, Ishan Gupta +47

Long-horizon, multi-agent language model (LM) simulations are widely proposed for studying social behavior, yet instruments to measure whether persona-conditioned agents maintain i…

cs.HC2026

PersonaEval: Persona-Based User Simulation for Evaluating Interactive Applications

Yifan Simon Liu, Qianfeng Wen, Yilan Fan +40

Real user studies are important for understanding how people interact with systems under test or already deployed. In practice, however, they are often costly, time-consuming, and…

cs.AR2026

KV-RM: Regularizing KV-Cache Movement for Static-Graph LLM Serving

Zhiqing Zhong, Zhijing Ye, Jian Zhang +3

Static-graph LLM decoders provide predictable launches, fixed tensor shapes, and low submission overhead, but online decoding exposes highly irregular KV-cache behavior: request le…

cs.AI20252 cited

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges

Haoran Lu, Luyang Fang, Ruidong Zhang +47

Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…

cs.HC2024

Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents

Bolun Sun, Yifan Zhou, Haiyun Jiang

This paper presents a novel application of large language models (LLMs) to enhance user comprehension of privacy policies through an interactive dialogue agent. We demonstrate that…