·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Newer Models, Same Advantage47m◆COMPUTER COPS: Inside the big business of selling AI to the police1h◆How Far Can Root Cause Analysis Go on Real-World Telemetry Data?8h◆Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling8h◆AI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized8h◆When Bots Join the Team: Bot Adoption and the Institutional Fabric of Open-Source Software Projects8h◆Experience Memory Graph: One-Shot Error Correction for Agents8h◆Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.08h◆LessonBench-V1: A Benchmark Dataset for Evaluating AI Lesson Generation Agents8h◆SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests8h◆CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion8h◆What Models Express, Suppress, and Resist: Auditing Open-Weight LLMs with Persona Vectors8h◆Reassessing Muon for Matrix Factorization8h◆Faithful Autoformalization of Natural Language Assertions8h◆Accuracy Without Grounding: Diagnosing Visual Dependency Dissociation in Video LLM Benchmarks8h◆Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains8h◆Privacy Preserving Recommender Systems Balancing Personalization with Privacy8h◆Efficient Text-to-Audio Generation via Pruning8h◆The Refusal Residue: When Probes Catch Alignment Faking and When They Don't8h◆Evaluation Ability Does Not Imply Optimization Utility: LLM-as-a-Judge Signals in Closed-Loop Table Recognition8h◆Newer Models, Same Advantage47m◆COMPUTER COPS: Inside the big business of selling AI to the police1h◆How Far Can Root Cause Analysis Go on Real-World Telemetry Data?8h◆Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling8h◆AI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized8h◆When Bots Join the Team: Bot Adoption and the Institutional Fabric of Open-Source Software Projects8h◆Experience Memory Graph: One-Shot Error Correction for Agents8h◆Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.08h◆LessonBench-V1: A Benchmark Dataset for Evaluating AI Lesson Generation Agents8h◆SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests8h◆CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion8h◆What Models Express, Suppress, and Resist: Auditing Open-Weight LLMs with Persona Vectors8h◆Reassessing Muon for Matrix Factorization8h◆Faithful Autoformalization of Natural Language Assertions8h◆Accuracy Without Grounding: Diagnosing Visual Dependency Dissociation in Video LLM Benchmarks8h◆Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains8h◆Privacy Preserving Recommender Systems Balancing Personalization with Privacy8h◆Efficient Text-to-Audio Generation via Pruning8h◆The Refusal Residue: When Probes Catch Alignment Faking and When They Don't8h◆Evaluation Ability Does Not Imply Optimization Utility: LLM-as-a-Judge Signals in Closed-Loop Table Recognition8h◆
News/ESC: Emotional Self-Correction for Reliable Vision-Language Models
arxiv
PublishedJuly 3, 2026 at 4:00 AM

ESC: Emotional Self-Correction for Reliable Vision-Language Models

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

arXiv:2607.02089v1 Announce Type: cross Abstract: Vision-language models (VLMs) have achieved strong performance across diverse multimodal tasks, yet they remain vulnerable to unreliable reasoning. Existing self-correction methods mitigate these issues but typically rely on post-training or carefull

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
arxivHow Far Can Root Cause Analysis Go on Real-World Telemetry Data?8harxivMulti-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling8harxivAI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized8harxivWhen Bots Join the Team: Bot Adoption and the Institutional Fabric of Open-Source Software Projects8h
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