1 citations · 1 across the 6 of their papers we have counts for
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Why Bother Me Again? Benchmarking Personal Agent Memory for Interaction Preferences
Jialin Li, Zhenhao Chen, Hanjun Luo +1
Personal intelligence systems are taking on increasingly complex everyday tasks, yet repeated questions, unnecessary confirmations, and unwanted outreach can turn capable assistanc…
ANIMASK: What the Model Contributes to Role Play in Simulated Story Worlds
Xiucheng Zhang, Zhuoning Xu, Hanjun Luo +3
When a language model plays a character, the observed behavior reflects both the assigned persona and the default dispositions of the actor model itself. Existing evaluations test…
AutoCRAT: Within-trajectory Joint Control of Stochasticity and Compute for LLM Reasoning
Hanjun Luo, Qiushi Liu, Jingya Zhang +8
Large language models (LLMs) achieve strong reasoning performance, which depends critically on inference-time decisions. Yet these decisions are commonly handled by static, one-siz…
AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
Hanjun Luo, Zhimu Huang, Sylvia Chung +6
Text-to-image (T2I) systems increasingly rely on upstream prompters, either humans or multimodal large language models (MLLMs), to translate user intent into detailed prompts. Yet…
BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models
Hanjun Luo, Zhimu Huang, Haoyu Huang +5
Text-to-Image (T2I) generative models have revolutionized content creation, yet they inherently risk amplifying societal biases. While sociological research provides systematic cla…
PrefIx: Understand and Adapt to User Preference in Human-Agent Interaction
Jialin Li, Zhenhao Chen, Hanjun Luo +1
LLM-based agents can complete tasks correctly yet still frustrate users through poor interaction patterns, such as excessive confirmations, opaque reasoning, or misaligned pacing.…