5 papers
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…
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
Zhenhao Chen, Yongqiang Chen, Chenxi Liu +7
Building AI Scientist agents with Large Language Models (LLMs) has recently attracted growing attention. Since scientific discovery fundamentally relies on uncovering causal relati…
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…
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.…
Improving Personalisation in Valence and Arousal Prediction using Data Augmentation
Munachiso Nwadike, Jialin Li, Hanan Salam
In the field of emotion recognition and Human-Machine Interaction (HMI), personalised approaches have exhibited their efficacy in capturing individual-specific characteristics and…