13 citations · 23 across the 8 of their papers we have counts for
9 papers
ScreenHaystack: Finding Blind Zones in GUI Grounding
Chenyue Li, Xiaoxiao Sun, Yubo Deng +3
We introduce ScreenHaystack, a dynamic needle-in-a-haystack benchmark for evaluating spatial reliability in GUI grounding. Instead of testing each target at a fixed position, Scree…
Human Values Matter: Investigating How Misalignment Shapes Collective Behaviors in LLM Agent Communities
Xiangxu Zhang, Jiamin Wang, Qinlin Zhao +6
As LLMs become increasingly integrated into human society, evaluating their orientations on human values from social science has drawn growing attention. Nevertheless, it is still…
On the Dynamics of Multi-Agent LLM Communities Driven by Value Diversity
Muhua Huang, Qinlin Zhao, Xiaoyuan Yi +1
As Large Language Models (LLM) based multi-agent systems become increasingly prevalent, the collective behaviors, e.g., collective intelligence, of such artificial communities have…
Knowing Your Uncertainty -- On the application of LLM in social sciences
Bolun Zhang, Linzhuo Li, Yunqi Chen +4
Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and designed stochastic elements in inference po…
General Scales Unlock AI Evaluation with Explanatory and Predictive Power
Lexin Zhou, Lorenzo Pacchiardi, Fernando Martínez-Plumed +23
Ensuring safe and effective use of AI requires understanding and anticipating its performance on novel tasks, from advanced scientific challenges to transformed workplace activitie…
AgentReview: Exploring Peer Review Dynamics with LLM Agents
Yiqiao Jin, Qinlin Zhao, Yiyang Wang +4
Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exploration and statistics of exist…
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao +2
Evaluation of large language models (LLMs) has raised great concerns in the community due to the issue of data contamination. Existing work designed evaluation protocols using well…
PromptBench: A Unified Library for Evaluation of Large Language Models
Kaijie Zhu, Qinlin Zhao, Hao Chen +2
The evaluation of large language models (LLMs) is crucial to assess their performance and mitigate potential security risks. In this paper, we introduce PromptBench, a unified libr…
CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents
Qinlin Zhao, Jindong Wang, Yixuan Zhang +4
Large language models (LLMs) have been widely used as agents to complete different tasks, such as personal assistance or event planning. While most of the work has focused on coope…