·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response6h◆Learning Transferable Latent User Preferences for Human-Aligned Decision Making6h◆Beyond a Single Direction: Chain-of-Thought Disrupts Simple Steering of Refusal6h◆Teaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization6h◆Repair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents6h◆AIMO Interpretability Challenge6h◆IndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD6h◆ECHO: An Auditable Dual-Path Memory System for Long-Horizon Agents6h◆Ethical LLM-Assisted Research: A Framework for Responsible Delegation, Verification, and Epistemic Value6h◆Differential Functionalism: Jacobians Shape the Structure of Phenomenal Experience6h◆Unified Agentic Video Editing Across Levels of Complexity and Creativity6h◆ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models6h◆Diffusion Subgoal Planning for Long-Horizon Offline Goal-Conditioned Reinforcement Learning6h◆Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations6h◆Not Self-Decidable: LLMs Cannot Draw the Boundary of What an Agent Verifier Can Check6h◆TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU6h◆AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment6h◆HSPR: Recovering Software-Agent Benchmark Scores via Hierarchical Posterior Inference6h◆Typhoon: Gradient-Based Task-Specific Masking for Masked Language Models6h◆Entropic perspective on AI resilience, data-minimal learning and optimal control6h◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response6h◆Learning Transferable Latent User Preferences for Human-Aligned Decision Making6h◆Beyond a Single Direction: Chain-of-Thought Disrupts Simple Steering of Refusal6h◆Teaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization6h◆Repair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents6h◆AIMO Interpretability Challenge6h◆IndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD6h◆ECHO: An Auditable Dual-Path Memory System for Long-Horizon Agents6h◆Ethical LLM-Assisted Research: A Framework for Responsible Delegation, Verification, and Epistemic Value6h◆Differential Functionalism: Jacobians Shape the Structure of Phenomenal Experience6h◆Unified Agentic Video Editing Across Levels of Complexity and Creativity6h◆ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models6h◆Diffusion Subgoal Planning for Long-Horizon Offline Goal-Conditioned Reinforcement Learning6h◆Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations6h◆Not Self-Decidable: LLMs Cannot Draw the Boundary of What an Agent Verifier Can Check6h◆TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU6h◆AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment6h◆HSPR: Recovering Software-Agent Benchmark Scores via Hierarchical Posterior Inference6h◆Typhoon: Gradient-Based Task-Specific Masking for Masked Language Models6h◆Entropic perspective on AI resilience, data-minimal learning and optimal control6h◆
News/DStill: Trajectory Consistency Distillation for Accelerated One-Step Drafting in Block Diffusion Speculative Decoding
arxiv
PublishedOctober 21, 2026 at 4:00 AM

DStill: Trajectory Consistency Distillation for Accelerated One-Step Drafting in Block Diffusion Speculative Decoding

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

arXiv:2610.27379v1 Announce Type: new Abstract: Block-diffusion speculative decoding accelerates large language model inference by drafting multiple tokens in parallel. However, one-step drafting in discrete diffusion is limited by token factorization error: each token is predicted from the same mas

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
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response6harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making6harxivBeyond a Single Direction: Chain-of-Thought Disrupts Simple Steering of Refusal6harxivTeaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization6h
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