·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Retrieval Augmented Generation Compositionality5h◆VeriEvolve: Evaluator-First Evolution for Tool-Using Agents5h◆TNODEV: Toolbox for Neural ODE Verification5h◆Learning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding5h◆On the Expressive Power and Limitations of Multi-Layer SSMs5h◆From Weather to Enhanced Weathering: Weather Foundation Models for Carbon Dioxide Removal at Operational Scale5h◆Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression5h◆A Generalisation Signal Need Not Be a Model-Selection Signal5h◆Mitigating Reward Hacking in Realistic Scenarios Through Representation Engineering5h◆EgoHand: Monocular 3D Hand Reconstruction from Egocentric Video5h◆Learning to Incentivise: Using Reinforcement Learning for Sustainable Urban Mobility5h◆ChemBART: Pre-training a Reaction Language Model for Comprehensive Synthesis Planning5h◆Kernel-Managed Shared Memory for System-Wide Personalization5h◆Uber rival inDrive eyes 2027 robotaxi tests in Central Asia with Pony.ai and Nvidia5h◆Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?5h◆AnnoCaseLaw: Legal Annotation Benchmark of Civil Negligence5h◆Improved Training of Strong Stochastic Flow Maps5h◆Think Harder Where It Matters: Item-Level Adaptive Recursion for Sequential Recommendation5h◆HyperDrone: Simulation-to-Reality Transfer at Millions of Frames per Second5h◆Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection5h◆Retrieval Augmented Generation Compositionality5h◆VeriEvolve: Evaluator-First Evolution for Tool-Using Agents5h◆TNODEV: Toolbox for Neural ODE Verification5h◆Learning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding5h◆On the Expressive Power and Limitations of Multi-Layer SSMs5h◆From Weather to Enhanced Weathering: Weather Foundation Models for Carbon Dioxide Removal at Operational Scale5h◆Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression5h◆A Generalisation Signal Need Not Be a Model-Selection Signal5h◆Mitigating Reward Hacking in Realistic Scenarios Through Representation Engineering5h◆EgoHand: Monocular 3D Hand Reconstruction from Egocentric Video5h◆Learning to Incentivise: Using Reinforcement Learning for Sustainable Urban Mobility5h◆ChemBART: Pre-training a Reaction Language Model for Comprehensive Synthesis Planning5h◆Kernel-Managed Shared Memory for System-Wide Personalization5h◆Uber rival inDrive eyes 2027 robotaxi tests in Central Asia with Pony.ai and Nvidia5h◆Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?5h◆AnnoCaseLaw: Legal Annotation Benchmark of Civil Negligence5h◆Improved Training of Strong Stochastic Flow Maps5h◆Think Harder Where It Matters: Item-Level Adaptive Recursion for Sequential Recommendation5h◆HyperDrone: Simulation-to-Reality Transfer at Millions of Frames per Second5h◆Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection5h◆
News/Reverse-KL Policy Distillation: Statistical Guarantees and Limits
arxiv
PublishedOctober 23, 2026 at 4:00 AM

Reverse-KL Policy Distillation: Statistical Guarantees and Limits

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2610.30844v1 Announce Type: new Abstract: Reverse Kullback-Leibler (KL) distillation has shown empirical promise for training language models, but its statistical guarantees and limits remain poorly understood. In particular, the effects of two design choices remain unclear: Does access to the

Stay posted· Newsletter

Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivRetrieval Augmented Generation Compositionality5harxivVeriEvolve: Evaluator-First Evolution for Tool-Using Agents5harxivTNODEV: Toolbox for Neural ODE Verification5harxivLearning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding5h
The Bubble Brief
MON · WED · FRI

Read AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Originally published on arxiv ↗
PrivacyTermsRefundsLegal notice|AboutMethodologyContact

© 2026 Databubble

Built by Marouane Gazouzi · Readyo, AI interview coach

HomeModelsNews