1 citations · 1 across the 6 of their papers we have counts for
8 papers
DecisionRobust: Benchmarking Robustness for JEV Style Decision Models Across Text and Vision
Yifan Lan, Zhongye Liu, Yurui Chang +4
Emerging decision models such as JEV provide typed interfaces that map task instructions and observations directly to choices, judgments, and scores. As these models are increasing…
From Narrative to Auditable Forecasts: A Structured Scaffold for Agentic Forecasting
Yuanpu Cao, Yongkang Du, Yurui Chang +2
LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events. However, current agentic forec…
ForecastCompass: Guiding Agentic Forecasting with Adaptive Factor Memory
Yurui Chang, Yongkang Du, Yuanpu Cao +2
Agentic forecasting is important for decision-making in dynamic environments, but it remains challenging because agents must reason from incomplete, time-limited evidence and produ…
Mitigating topology biases in Graph Diffusion via Counterfactual Intervention
Wendi Wang, Jiaxi Yang, Yongkang Du +1
Graph diffusion models have gained significant attention in graph generation tasks, but they often inherit and amplify topology biases from sensitive attributes (e.g. gender, age,…
CARV: A Diagnostic Benchmark for Compositional Analogical Reasoning in Multimodal LLMs
Yongkang Du, Xiaohan Zou, Minhao Cheng +1
Analogical reasoning tests a fundamental aspect of human cognition: mapping the relation from one pair of objects to another. Existing evaluations of this ability in multimodal lar…
Controllable Pareto Trade-off between Fairness and Accuracy
Yongkang Du, Jieyu Zhao, Yijun Yang +1
The fairness-accuracy trade-off is a key challenge in NLP tasks. Current work focuses on finding a single "optimal" solution to balance the two objectives, which is limited conside…
FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks
Yongkang Du, Jen-tse Huang, Jieyu Zhao +1
Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critical concern. While LLMs are train…
Self-Contradictory Reasoning Evaluation and Detection
Ziyi Liu, Soumya Sanyal, Isabelle Lee +4
In a plethora of recent work, large language models (LLMs) demonstrated impressive reasoning ability, but many proposed downstream reasoning tasks only focus on final answers. Two…