·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
SpaceX has an AI device prototype, and it sure sounds phone-ish2h◆Ashton Kutcher leaving Sound Ventures to launch new VC firm with Morgan Beller2h◆The latest AI news we announced in June 20263h◆Cloudflare’s new policy pushes AI companies to pay for publishers’ content3h◆New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.5h◆LLMs are stuck in a groupthink groove. This startup is trying to get them out.6h◆Venice AI becomes a unicorn with $65M Series A as its privacy-first AI platform takes off6h◆Gemini Spark, Google’s agentic assistant, is now available on Mac6h◆Builders Stage agenda revealed: Practical strategies for scaling startups at TechCrunch Disrupt 20267h◆Meta, like SpaceX, looks to turn excess AI compute into cash7h◆Google built a great smart speaker, but Gemini isn’t ready for it9h◆Surprise as a Signal for Plasticity and Metacognition17h◆SwiftAudio: Data-Efficient Caption-Only Distillation for One-Step Text-to-Audio Diffusion-based Generation17h◆3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance17h◆Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian17h◆JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering17h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement17h◆Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling17h◆From Propositional to Perceptual Asymmetry: Extending Frictive Policy Optimization to Asymmetric Partial Information Dialogue17h◆Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments17h◆SpaceX has an AI device prototype, and it sure sounds phone-ish2h◆Ashton Kutcher leaving Sound Ventures to launch new VC firm with Morgan Beller2h◆The latest AI news we announced in June 20263h◆Cloudflare’s new policy pushes AI companies to pay for publishers’ content3h◆New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.5h◆LLMs are stuck in a groupthink groove. This startup is trying to get them out.6h◆Venice AI becomes a unicorn with $65M Series A as its privacy-first AI platform takes off6h◆Gemini Spark, Google’s agentic assistant, is now available on Mac6h◆Builders Stage agenda revealed: Practical strategies for scaling startups at TechCrunch Disrupt 20267h◆Meta, like SpaceX, looks to turn excess AI compute into cash7h◆Google built a great smart speaker, but Gemini isn’t ready for it9h◆Surprise as a Signal for Plasticity and Metacognition17h◆SwiftAudio: Data-Efficient Caption-Only Distillation for One-Step Text-to-Audio Diffusion-based Generation17h◆3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance17h◆Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian17h◆JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering17h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement17h◆Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling17h◆From Propositional to Perceptual Asymmetry: Extending Frictive Policy Optimization to Asymmetric Partial Information Dialogue17h◆Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments17h◆
News/When the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialogue
arxiv
PublishedJuly 1, 2026 at 4:00 AM
—neutral

When the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialogue

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

arXiv:2606.31307v1 Announce Type: new Abstract: Large language models used in task-oriented dialogue often produce fluent but unsafe responses when backend database calls fail, return empty results, or surface mismatched information, inventing venues, confirmations, or booking details not grounded i

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
arxivSurprise as a Signal for Plasticity and Metacognition17harxivSwiftAudio: Data-Efficient Caption-Only Distillation for One-Step Text-to-Audio Diffusion-based Generation17harxiv3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance17harxivCross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian17h
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