3 papers
cs.LG2026
RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement
Will LeVine, Brendan Evers, Sam Saltwick +1
Iterative self-refinement is a popular inference-time reliability technique, but its effectiveness in code-mode tool use depends heavily on the structure of the feedback signal: un…
cs.CV2019
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains
Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung +1
Data dependent regularization is known to benefit a wide variety of problems in machine learning. Often, these regularizers cannot be easily decomposed into a sum over a finite num…
cs.LG2019
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations
Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh +2
Rectified Linear Units (ReLUs) are among the most widely used activation function in a broad variety of tasks in vision. Recent theoretical results suggest that despite their excel…