11 papers
Learning When to Trust via Selective Context Preference Optimization
Xian Sun, Wei Chow, Yingshuo Wang +4
Language models increasingly condition their answers on external signals, and a single misleading one can turn a correct answer wrong. The obvious remedy, training models to resist…
Data Pyramid for Embodied Manipulation: A Survey
Yifan Ye, Yankai Fu, Yaoxu Lv +26
Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…
The Moving Target: A Longitudinal Audit of Trust-Benchmark Score Drift Across Open-Source Chat LLM Release Lines
Zhichao Fan, Yanhang Li, Zexin Zhuang +2
Trust-benchmark scores reported on a chat-LLM release line are often carried across several checkpoints of the same line, as if the underlying model had not shifted between release…
Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting
Yingshuo Wang, Xian Sun, Lingdong Kong +4
Standard benchmarks evaluate time series foundation models (TSFMs) using aggregate metrics, but these can mask severe failures in critical operating regimes. We introduce regime-st…
Embedding Foundation Model Predictions in Discrete-Choice Models with Structural Guarantees
Yingshuo Wang, Xian Sun, Yanhang Li +2
Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks require: raising a price can increa…
Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation
Xian Sun, Wei Gao, Yingshuo Wang +9
Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support…