·
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 Response1h◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training1h◆Large language model and reinforcement learning based autonomous construction and progress updates1h◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring1h◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution1h◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing1h◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning1h◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System1h◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability1h◆Physical AI: Concepts, Techniques, and Challenges1h◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems1h◆A general-purpose System One decision model for clinical records1h◆EDMA: Entropy-Driven Multimodal Answering1h◆Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations1h◆TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation1h◆When PTQ Calibration Helps or Hurts: Dose-Driven Collapse and Validation-Gated Abstention in Quantized Text Embedders1h◆Unified Sharp Bounds on Probabilities of Causation1h◆ProMemAgent: Long-Horizon Proactive Assistance with Context-Aware Prospective Memory from Sensory Perceptions1h◆Harness Self-Evolution for Long-Horizon Terminal Agents1h◆Ask to Distill: Learning to Synthesize Data for On-Policy Distillation1h◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response1h◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training1h◆Large language model and reinforcement learning based autonomous construction and progress updates1h◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring1h◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution1h◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing1h◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning1h◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System1h◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability1h◆Physical AI: Concepts, Techniques, and Challenges1h◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems1h◆A general-purpose System One decision model for clinical records1h◆EDMA: Entropy-Driven Multimodal Answering1h◆Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations1h◆TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation1h◆When PTQ Calibration Helps or Hurts: Dose-Driven Collapse and Validation-Gated Abstention in Quantized Text Embedders1h◆Unified Sharp Bounds on Probabilities of Causation1h◆ProMemAgent: Long-Horizon Proactive Assistance with Context-Aware Prospective Memory from Sensory Perceptions1h◆Harness Self-Evolution for Long-Horizon Terminal Agents1h◆Ask to Distill: Learning to Synthesize Data for On-Policy Distillation1h◆
News/LSC-DPO: Learning-Signal-Controlled Direct Preference Optimization
arxiv
PublishedOctober 8, 2026 at 4:00 AM
—neutral

LSC-DPO: Learning-Signal-Controlled Direct Preference Optimization

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

arXiv:2610.07592v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) has become a standard reward-model-free approach for aligning language models with preference data. However, as the scaled preference margin grows during training, the logistic DPO loss becomes progressively less se

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 Response1harxivNavalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training1harxivLarge language model and reinforcement learning based autonomous construction and progress updates1harxivMedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring1h
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