54 citations · 79 across the 14 of their papers we have counts for
14 papers
MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs
Kevin Wang, Anna Thöni, Benjamin Kempinski +50
Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…
Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs
Yue Huang, Haomin Zhuang, Jiayi Ye +6
Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yielding safer-on-paper yet less us…
MultiRef: Controllable Image Generation with Multiple Visual References
Ruoxi Chen, Dongping Chen, Siyuan Wu +6
Visual designers naturally draw inspiration from multiple visual references, combining diverse elements and aesthetic principles to create artwork. However, current image generativ…
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search
Yanbo Wang, Zixiang Xu, Yue Huang +6
Large Language Models (LLMs) often struggle to maintain their original performance when faced with semantically coherent but task-irrelevant contextual information. Although prior…
1+1>2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?
Yue Huang, Chenrui Fan, Yuan Li +4
Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they e…
DataGen: Unified Synthetic Dataset Generation via Large Language Models
Yue Huang, Siyuan Wu, Chujie Gao +8
Large Language Models (LLMs) such as GPT-4 and Llama3 have significantly impacted various fields by enabling high-quality synthetic data generation and reducing dependence on expen…
GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
Dongping Chen, Yue Huang, Siyuan Wu +17
Recently, Multimodal Large Language Models (MLLMs) have been used as agents to control keyboard and mouse inputs by directly perceiving the Graphical User Interface (GUI) and gener…
HonestLLM: Toward an Honest and Helpful Large Language Model
Chujie Gao, Siyuan Wu, Yue Huang +6
Large Language Models (LLMs) have achieved remarkable success across various industries due to their exceptional generative capabilities. However, for safe and effective real-world…
WebCode2M: A Real-World Dataset for Code Generation from Webpage Designs
Yi Gui, Zhen Li, Yao Wan +10
Automatically generating webpage code from webpage designs can significantly reduce the workload of front-end developers, and recent Multimodal Large Language Models (MLLMs) have s…
NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries
Wei Zhao, Zhitao Hou, Siyuan Wu +6
Writing formulas on spreadsheets, such as Microsoft Excel and Google Sheets, is a widespread practice among users performing data analysis. However, crafting formulas on spreadshee…
I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench
Yuan Li, Yue Huang, Yuli Lin +3
Do large language models (LLMs) exhibit any forms of awareness similar to humans? In this paper, we introduce AwareBench, a benchmark designed to evaluate awareness in LLMs. Drawin…
TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang +67
Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…
MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use
Yue Huang, Jiawen Shi, Yuan Li +8
Large language models (LLMs) have garnered significant attention due to their impressive natural language processing (NLP) capabilities. Recently, many studies have focused on the…