3 citations · 4 across the 17 of their papers we have counts for
8 papers · 1 filter
Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules
Liviu Aolaritei, Lucas Lévy, Francis Bach +1
Stochastic gradient descent (SGD) is typically analyzed at a deterministic horizon chosen before the algorithm is run, even though practical stopping decisions are made adaptively…
Eigenvalue Calibration for Semantic Embeddings of Large Language Models
Sebastian G. Gruber, Nassim Walha, Francis Bach +1
Uncertainty quantification is central to the reliable deployment of large language models (LLMs), and eigenvalues of semantic embeddings have recently emerged as a key tool in stat…
DecompRL: Solving Harder Problems by Learning Modular Code Generation
Juliette Decugis, Fabian Gloeckle, Francis Bach +2
How can Large Language Models (LLMs) solve problems they currently cannot? Repeated sampling scales test-time compute but GPU cost grows linearly with attempts, while reinforcement…
CalArena: A Large-Scale Post-Hoc Calibration Benchmark
Eugène Berta, David Holzmüller, Francis Bach +1
Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibration provides a simple and wi…
Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
Sacha Braun, Michael I. Jordan, Francis Bach
Constructing minimum-volume prediction regions that satisfy conditional coverage is a fundamental challenge in multivariate regression. Standard approaches rely on explicitly estim…
Explaining and Preventing Alignment Collapse in Iterative RLHF
Etienne Gauthier, Francis Bach, Michael I. Jordan
Reinforcement learning from human feedback (RLHF) typically assumes a static or non-strategic reward model (RM). In iterative deployment, however, the policy generates the data on…
V-ECE: Estimating General Expected Calibration Errors
Eugène Berta, Sacha Braun, David Holzmüller +2
In probabilistic classification, calibration error (CE) measures the average divergence of predicted probabilities from , the true class distribution for…
Anytime Detection of Strategic Deviations in Multi-Agent Systems
Etienne Gauthier, Francis Bach, Michael I. Jordan
In many multi-agent systems, agents interact repeatedly and are expected to settle into stable, rational behavior over time. Yet in practice, behavior often drifts, and detecting s…