·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Meta AI director Rohit Patel leaves to take on Microsoft Office and Google Workspace1h◆Apple is adding an AI chatbot to Pages, Keynote, and Numbers2h◆Japan internet giant GMO says hackers posted stolen customer data2h◆Opera introduces a new web standard to let users deploy AI locally in their browser3h◆General Compute raises $100 million Series A, countering the neocloud disaster narrative3h◆Industrial Intelligence: The next growth opportunity for manufacturing4h◆Nvidia backs Indian startup helping companies run AI models with fewer GPUs5h◆Data center backlash is uniting America6h◆When Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12h◆Query-Driven Learning for Lifted Reasoning12h◆The Social World Model Evaluation Gap12h◆Conviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h◆The Value of Memory in Language Agents12h◆Synthetic linguistic data12h◆MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation12h◆NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting12h◆RobotAgentBench: Towards Open-world Robot Autonomy12h◆Folding Pooled Usage Examples into the Tool Index Lowers Retrieval of Unused Tools12h◆Compatible Likelihoods for Flow Matching on Manifolds12h◆Foundations of the Scaling Law12h◆Meta AI director Rohit Patel leaves to take on Microsoft Office and Google Workspace1h◆Apple is adding an AI chatbot to Pages, Keynote, and Numbers2h◆Japan internet giant GMO says hackers posted stolen customer data2h◆Opera introduces a new web standard to let users deploy AI locally in their browser3h◆General Compute raises $100 million Series A, countering the neocloud disaster narrative3h◆Industrial Intelligence: The next growth opportunity for manufacturing4h◆Nvidia backs Indian startup helping companies run AI models with fewer GPUs5h◆Data center backlash is uniting America6h◆When Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12h◆Query-Driven Learning for Lifted Reasoning12h◆The Social World Model Evaluation Gap12h◆Conviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h◆The Value of Memory in Language Agents12h◆Synthetic linguistic data12h◆MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation12h◆NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting12h◆RobotAgentBench: Towards Open-world Robot Autonomy12h◆Folding Pooled Usage Examples into the Tool Index Lowers Retrieval of Unused Tools12h◆Compatible Likelihoods for Flow Matching on Manifolds12h◆Foundations of the Scaling Law12h◆
News/GiPL: Generative augmented iterative Pseudo-Labeling for Cross-Domain Few-Shot Object Detection
arxiv
PublishedMay 29, 2026 at 4:00 AM
▲bullish

GiPL: Generative augmented iterative Pseudo-Labeling for Cross-Domain Few-Shot Object Detection

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

arXiv:2605.29539v1 Announce Type: cross Abstract: Vision-language foundation models have shown promising zero-shot generalization for Cross-Domain Few-Shot Object Detection (CD-FSOD). However, they face two critical challenges in fine-tuning: insufficient support set utilization due to sparse single

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
Mentioned models
01
  • 01
    GiPL
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#computer-vision#object-detection#few-shot-learning

No replies yet. Be first.

Mentioned models
01
  • 01
    GiPL
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#computer-vision#object-detection#few-shot-learning

Related coverage

More from ARXIV
arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12harxivQuery-Driven Learning for Lifted Reasoning12harxivThe Social World Model Evaluation Gap12harxivConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h
The Bubble Brief
MON · WED · FRI

Read computer-vision 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