2 papers
cs.LG2025
Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood
Gilhyun Nam, Taewon Kim, Joonhyun Jeong +1
Test-time adaptation (TTA) enables efficient adaptation of deployed models, yet it often leads to poorly calibrated predictive uncertainty - a critical issue in high-stakes domains…
cs.AI2025
Co-Evolving Agents: Learning from Failures as Hard Negatives
Yeonsung Jung, Trilok Padhi, Sina Shaham +4
The rapid progress of large foundation models has accelerated the development of task-specialized agents across diverse domains. However, the effectiveness of agents remains tightl…