·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Automatic Sentence Completion Using Bengali Audio Speech with a Transformer-Based Early Speech Recognition System2h◆What Should We Remove? Evaluating the Reliability and Costs of RLVR Data Decontamination2h◆FGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization2h◆LLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework2h◆Making every stage of medical device document assessment with large language models deterministic2h◆VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation2h◆DPA-MoE: A Runtime Precision Control Framework for MoE Inference2h◆HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding2h◆Translation Circuit Discovery and Targeted Optimization for Low-Resource Multilingual Translation2h◆OPRD: On-Policy Reminder Distillation for Long-Horizon Coding Agents2h◆Writability and the Pathway: A Controlled Study of Knowledge Injection into Addressed Memory2h◆ContextLift: Breaking the Spurious Correlation Behind Conditional Emergent Misalignment2h◆Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods2h◆Content associations with answer selection and engagement in supply chain community question answering2h◆Beyond Context Length: Characterising the Difficulty of Long-Context Reasoning2h◆The Right Byte First: How UTF-16 Helps Multilingual Boundary Prediction2h◆Patch where the text is new: a compression view of where byte-level models should spend compute2h◆Unfragmenting Nawatl NMT: Single-Variant Specialization for Masewalkopa2h◆Training Reasoning Models to Generate Diverse Scientific Ideas2h◆OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling2h◆Automatic Sentence Completion Using Bengali Audio Speech with a Transformer-Based Early Speech Recognition System2h◆What Should We Remove? Evaluating the Reliability and Costs of RLVR Data Decontamination2h◆FGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization2h◆LLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework2h◆Making every stage of medical device document assessment with large language models deterministic2h◆VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation2h◆DPA-MoE: A Runtime Precision Control Framework for MoE Inference2h◆HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding2h◆Translation Circuit Discovery and Targeted Optimization for Low-Resource Multilingual Translation2h◆OPRD: On-Policy Reminder Distillation for Long-Horizon Coding Agents2h◆Writability and the Pathway: A Controlled Study of Knowledge Injection into Addressed Memory2h◆ContextLift: Breaking the Spurious Correlation Behind Conditional Emergent Misalignment2h◆Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods2h◆Content associations with answer selection and engagement in supply chain community question answering2h◆Beyond Context Length: Characterising the Difficulty of Long-Context Reasoning2h◆The Right Byte First: How UTF-16 Helps Multilingual Boundary Prediction2h◆Patch where the text is new: a compression view of where byte-level models should spend compute2h◆Unfragmenting Nawatl NMT: Single-Variant Specialization for Masewalkopa2h◆Training Reasoning Models to Generate Diverse Scientific Ideas2h◆OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling2h◆
News/DeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents
arxiv
PublishedOctober 5, 2026 at 4:00 AM
—neutral

DeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents

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

arXiv:2610.02320v1 Announce Type: cross Abstract: Computer-use agents need to reliably ground action targets in complex desktop scenes, where multiple applications, overlapping windows, and visually similar controls compete for attention. Existing training data rarely pair such scenes with dense ann

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
arxivAutomatic Sentence Completion Using Bengali Audio Speech with a Transformer-Based Early Speech Recognition System2harxivWhat Should We Remove? Evaluating the Reliability and Costs of RLVR Data Decontamination2harxivFGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization2harxivLLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework2h
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