·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
The sameness problem behind those unappetizing AI-generated menus4h◆CulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning4h◆Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluation4h◆X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System4h◆A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors4h◆Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach4h◆Subspace Inference Enables Efficient Active Reward Learning from Preferences4h◆PCBWorld: A Benchmark Environment for Engine-Grounded PCB Design Automation4h◆Identifying AI Web Scrapers Using Canary Tokens4h◆PalmClaw: A Native On-Device Agent Framework for Mobile Phones4h◆Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition4h◆MemoryLACE: Memory Lifecycle-Aware Consolidation and Evidence Retrieval4h◆When Retrieval Helps: Selective Retrieval for Single-Turn Mental-Health QA4h◆ALRA: Adaptive Local Relational Alignment for Logit-Based Pre-training Distillation of Autoregressive Language Models4h◆VestigeKV: The NoPE-MLA KV Cache Carries Its Own Eviction Signal in a Vestigial Branch4h◆Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG4h◆ExecRetrieval: Measuring the Functional-Correctness Gap in Code-Embedding Retrieval4h◆Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models4h◆The Age of Curiosity Meets the Age of AI: Benchmarking Child Safety in Large Language Models4h◆Expert-Aware Causal Tracing of Factual Recall in Sparse MoE Language Models4h◆The sameness problem behind those unappetizing AI-generated menus4h◆CulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning4h◆Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluation4h◆X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System4h◆A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors4h◆Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach4h◆Subspace Inference Enables Efficient Active Reward Learning from Preferences4h◆PCBWorld: A Benchmark Environment for Engine-Grounded PCB Design Automation4h◆Identifying AI Web Scrapers Using Canary Tokens4h◆PalmClaw: A Native On-Device Agent Framework for Mobile Phones4h◆Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition4h◆MemoryLACE: Memory Lifecycle-Aware Consolidation and Evidence Retrieval4h◆When Retrieval Helps: Selective Retrieval for Single-Turn Mental-Health QA4h◆ALRA: Adaptive Local Relational Alignment for Logit-Based Pre-training Distillation of Autoregressive Language Models4h◆VestigeKV: The NoPE-MLA KV Cache Carries Its Own Eviction Signal in a Vestigial Branch4h◆Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG4h◆ExecRetrieval: Measuring the Functional-Correctness Gap in Code-Embedding Retrieval4h◆Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models4h◆The Age of Curiosity Meets the Age of AI: Benchmarking Child Safety in Large Language Models4h◆Expert-Aware Causal Tracing of Factual Recall in Sparse MoE Language Models4h◆
News/DLM-One: Diffusion Language Models for One-Step Sequence Generation
arxiv
PublishedSeptember 3, 2026 at 4:00 AM

DLM-One: Diffusion Language Models for One-Step Sequence Generation

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

arXiv:2506.00290v2 Announce Type: replace Abstract: This paper introduces DLM-One, a score-distillation-based framework for one-step sequence generation with continuous diffusion language models (DLMs). DLM-One eliminates iterative refinement by aligning the scores of a student model's outputs with

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

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

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
arxivCulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning4harxivProactive Service Agents: A Unified Decision Framework, Methods, and Evaluation4harxivX-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System4harxivA Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors4h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews