·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations3h◆Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence3h◆SimOPD: Relational Knowledge Transfer for On-Policy Distillation3h◆Generative Policy Improvement from Observational Data3h◆SkillBrowser: Selective Skill Exposure for Scalable Skill-Using Agents3h◆GEMS: Molecular Structure Elucidation as Learned Search over Isomer Graphs3h◆OwlSight: A Panoramic Monitor for Chain-of-Thought Reasoning3h◆Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability3h◆Hard Instances on Demand3h◆ARBOR: Locating Reasoning Failures in Long Chains of Thought through Reasoning State Tracking3h◆Aligning Language Models Towards Counterfactual Invariance3h◆Language Models Learn to Improve Language Models3h◆TUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in Typed Decision Models3h◆STAIF: A Stage-wise Optimization for Complex Instruction Following3h◆Q-Reflector: Learning GUI Action Reflection with Generated Conditions3h◆When Should Agents Check External State? Budgeting Observations for Stored Intentions3h◆RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees3h◆MultiWorldBench: Do Independently Controlled Views Describe One Shared World?3h◆Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration3h◆Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift3h◆GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations3h◆Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence3h◆SimOPD: Relational Knowledge Transfer for On-Policy Distillation3h◆Generative Policy Improvement from Observational Data3h◆SkillBrowser: Selective Skill Exposure for Scalable Skill-Using Agents3h◆GEMS: Molecular Structure Elucidation as Learned Search over Isomer Graphs3h◆OwlSight: A Panoramic Monitor for Chain-of-Thought Reasoning3h◆Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability3h◆Hard Instances on Demand3h◆ARBOR: Locating Reasoning Failures in Long Chains of Thought through Reasoning State Tracking3h◆Aligning Language Models Towards Counterfactual Invariance3h◆Language Models Learn to Improve Language Models3h◆TUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in Typed Decision Models3h◆STAIF: A Stage-wise Optimization for Complex Instruction Following3h◆Q-Reflector: Learning GUI Action Reflection with Generated Conditions3h◆When Should Agents Check External State? Budgeting Observations for Stored Intentions3h◆RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees3h◆MultiWorldBench: Do Independently Controlled Views Describe One Shared World?3h◆Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration3h◆Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift3h◆
News/When Is Enough Not Enough? Illusory Completion in Search Agents
arxiv
PublishedOctober 15, 2026 at 4:00 AM

When Is Enough Not Enough? Illusory Completion in Search Agents

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

arXiv:2602.07549v3 Announce Type: replace-cross Abstract: In agentic search, an LLM agent searches the web, reads the pages it finds, and decides what to look for next before returning an answer. But can we trust an answer simply because the agent returns it? Often not, and even a correct answer can

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
arxivGlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations3harxivAlgorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence3harxivSimOPD: Relational Knowledge Transfer for On-Policy Distillation3harxivGenerative Policy Improvement from Observational Data3h
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