6 citations · 14 across the 13 of their papers we have counts for
14 papers
Automatic multimodal UX improvement recommendations from LLM agent user simulations
Anu Chowdhury, Bin Wu, Hossein A. Rahmani +1
Evaluating user experience (UX) on live websites through user testing is expensive, subjective, and difficult to scale. LLM agents offer a promising route to automating UX testing…
Mitigating Context Interference for Reliable and Efficient Search Agents
Boyang Xue, Bin Wu, Shuofei Qiao +8
Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts…
AgentSearchBench: A Benchmark for AI Agent Search in the Wild
Bin Wu, Arastun Mammadli, Xiaoyu Zhang +1
The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable agents for a given task. Unli…
InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem
Shuofei Qiao, Yunxiang Wei, Xuehai Wang +10
The rapid evolution of Large Language Models has catalyzed a surge in scientific idea production, yet this leap has not been accompanied by a matching advance in idea evaluation. T…
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
Jinyuan Fang, Yanwen Peng, Xi Zhang +12
Recent advances in large language models have sparked growing interest in AI agents capable of solving complex, real-world tasks. However, most existing agent systems rely on manua…
PREF: Reference-Free Evaluation of Personalised Text Generation in LLMs
Xiao Fu, Hossein A. Rahmani, Bin Wu +3
Personalised text generation is essential for user-centric information systems, yet most evaluation methods overlook the individuality of users. We introduce \textbf{PREF}, a \text…
Boosting LLM's Molecular Structure Elucidation with Knowledge Enhanced Tree Search Reasoning
Xiang Zhuang, Bin Wu, Jiyu Cui +6
Molecular structure elucidation involves deducing a molecule's structure from various types of spectral data, which is crucial in chemical experimental analysis. While large langua…
Rethinking the Potential of Multimodality in Collaborative Problem Solving Diagnosis with Large Language Models
K. Wong, B. Wu, S. Bulathwela +1
Detecting collaborative and problem-solving behaviours from digital traces to interpret students' collaborative problem solving (CPS) competency is a long-term goal in the Artifici…
SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks
Tianhao Li, Jingyu Lu, Chuangxin Chu +12
Large language models (LLMs) have a transformative impact on a variety of scientific tasks across disciplines including biology, chemistry, medicine, and physics. However, ensuring…
Collaborative User Prompt for Personalized Generative Recommendation
Jerome Ramos, Bin Wu, Aldo Lipani
Large Language Models (LLMs) have become powerful foundations for generative recommender systems, framing recommendation tasks as text generation tasks. However, existing generativ…
Understanding the Role of User Profile in the Personalization of Large Language Models
Bin Wu, Zhengyan Shi, Hossein A. Rahmani +2
Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to enhance the performance on a wide range of tasks. However, the precise role of user profiles a…
Entropy-Based Decoding for Retrieval-Augmented Large Language Models
Zexuan Qiu, Zijing Ou, Bin Wu +3
Augmenting Large Language Models (LLMs) with retrieved external knowledge has proven effective for improving the factual accuracy of generated responses. Despite their success, ret…
Instruction Tuning With Loss Over Instructions
Zhengyan Shi, Adam X. Yang, Bin Wu +3
Instruction tuning plays a crucial role in shaping the outputs of language models (LMs) to desired styles. In this work, we propose a simple yet effective method, Instruction Model…
Graph Sampling-based Meta-Learning for Molecular Property Prediction
Xiang Zhuang, Qiang Zhang, Bin Wu +3
Molecular property is usually observed with a limited number of samples, and researchers have considered property prediction as a few-shot problem. One important fact that has been…