Apple Workshop on Privacy-Preserving Machine Learning: Interactive Differential Privacy in the OpenDP Library
AuthorsSalil Vadhan (Harvard University, U. Sydney)
Apple Workshop on Privacy-Preserving Machine Learning: Interactive Differential Privacy in the OpenDP Library
AuthorsSalil Vadhan (Harvard University, U. Sydney)
From Preferences to Principles: Rubric-Based Alignment for Grounded Knowledge Answers
August 27, 2026research area Methods and Algorithms, research area Speech and Natural Language Processing
Designing effective reward signals for open-domain question answering is challenging because high-quality responses must simultaneously satisfy multiple aspects of answer quality that are difficult to capture with a holistic scalar objective. We introduce a rubric-based reward framework that generates query-specific rubrics grounded in retrieved evidence and decomposed into multiple quality dimensions, providing fine-grained supervision during…
PROOF-Gen: From Optimized Data to Better Distillation
August 26, 2026research area Speech and Natural Language Processing, research area Tools, Platforms, Frameworksconference EMNLP
Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Post-training pipelines that drive shipped tool-calling agents re-run this stage on a daily or weekly cadence, paying the frontier-teacher cost each cycle, yet the mechanism is generate-and-filter (keep the teacher’s passing trajectories, discard the rest) and each cycle leaves behind the same hard…