1 citations · 1 across the 2 of their papers we have counts for
6 papers
WorldReasoner: Evaluating Whether Language Model Agents Forecast Events with Valid Reasoning
Yizhou Chi, Eric Chamoun, Zifeng Ding +1
Forecasting real-world events requires language-model agents to reason under uncertainty from incomplete, time-bounded information. Yet evaluating whether agents genuinely forecast…
SciPaths: Forecasting Pathways to Scientific Discovery
Eric Chamoun, Yizhou Chi, Yulong Chen +4
Scientific progress depends on sequences of enabling contributions, yet existing AI4Science benchmarks largely focus on citation prediction, literature retrieval, or idea generatio…
Demystifying Multi-Agent Debate: The Role of Confidence and Diversity
Xiaochen Zhu, Caiqi Zhang, Yizhou Chi +3
Multi-agent debate (MAD) is widely used to improve large language model (LLM) performance through test-time scaling, yet recent work shows that vanilla MAD often underperforms simp…
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning
Yizhou Chi, Yizhang Lin, Sirui Hong +9
Automated Machine Learning (AutoML) approaches encompass traditional methods that optimize fixed pipelines for model selection and ensembling, as well as newer LLM-based frameworks…
AMONGAGENTS: Evaluating Large Language Models in the Interactive Text-Based Social Deduction Game
Yizhou Chi, Lingjun Mao, Zineng Tang
Strategic social deduction games serve as valuable testbeds for evaluating the understanding and inference skills of language models, offering crucial insights into social science,…
CLARINET: Augmenting Language Models to Ask Clarification Questions for Retrieval
Yizhou Chi, Jessy Lin, Kevin Lin +1
Users often make ambiguous requests that require clarification. We study the problem of asking clarification questions in an information retrieval setting, where systems often face…