86 citations · 572 across the 39 of their papers we have counts for
44 papers
Learning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting
Siyu Zhou, Jialin Ouyang, Fan Xia +8
Continuous monitoring of generative AI systems requires detecting distribution shifts in the unstructured data they ingest and generate. Existing monitoring methods typically contr…
Extrapolating escape dynamics from non-escaping trajectories in Hamiltonian systems
Jianming Liu, Zhicheng Tong
Hamiltonian systems exhibit rich dynamical behaviors, among which escape is a typical phenomenon. Below the escape threshold, trajectories initiated inside the central potential we…
Admissible Diffusion for Multimodal Interventional Trajectories
Xing Han, Shravan Chaudhari, Jiarui Shao +2
Generating a plausible clinical trajectory does not establish what would happen under a different treatment. We present ADMIT, a framework combining irregular multimodal representa…
Counterfactual Self-Evolving Agents for Evidence-Grounded Reasoning
Xing Han, Yuxin Wang, Chen Chen +8
Self-play proposer--solver methods improve reasoning by generating tasks and learning from verified solutions. However, for evidence-identifiable tasks, where case-specific evidenc…
Toward Calibrated Mixture-of-Experts Under Distribution Shift
Gina Wong, Drew Prinster, Suchi Saria +2
Calibration aligns a model's predictive uncertainty with the frequencies of its empirical outcomes and is important for understanding and trusting reported probabilities. Recent wo…
MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling
Hsing-Huan Chung, Shijun Li, Yoav Wald +3
Multimodal irregular time series (MITS) consist of asynchronous and irregularly sampled observations from heterogeneous numerical and textual channels. In healthcare, for example,…