·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Romanized Arabic Across Dialects: Views, Usage Patterns, and Linguistic Variation5h◆Do AI-for-Science Agents Preserve Model Safety?5h◆Behaviour analysis for large language model-driven agents5h◆MPQ: A Message-Passing View of Post-Training Quantization5h◆$\Psi$-0.6: Adaptive Streams of Thought in a Unified Vision-Language World Model5h◆Not All Information Is Worth Asking For: Decision-Informed Information Seeking with LLMs5h◆Evidence-Grounded SLM Behavioral Prediction Architecture for Future Assistance Use5h◆POSEIDON: Scaling Training Environments for Scientific Agents from Code Repositories5h◆ALLMTS: Automated LLM-based Medical Triage System5h◆When Agents Fail: Model or Harness--Who's to Blame?5h◆LGMT: A Tool for Testing the Logical Reasoning Reliability of LLMs5h◆WiMoT: Replay-Free Continual Wi-Fi Sensing via Moment Transport5h◆Retiming Robot Demonstrations with a Learned Speed Prior5h◆Advancing SVD-based LLM Compression via Layer-Wise Error Model Search5h◆Validating the Comparison, Not Just the Scorer: Why Overall Accuracy Can Mislead in Interactive LLM Evaluation5h◆From Target Selection to Condition Reuse: Auditing Residual Interventions in Tool-Use Models5h◆Distributional Alignment of LLMs and Its Generalization Properties5h◆Collaborative In-Context Learning for Indoor Radio Map Estimation5h◆What Open-Source Projects Tell Their Coding Agents: A Census of AGENTS.md and CLAUDE.md5h◆Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data5h◆Romanized Arabic Across Dialects: Views, Usage Patterns, and Linguistic Variation5h◆Do AI-for-Science Agents Preserve Model Safety?5h◆Behaviour analysis for large language model-driven agents5h◆MPQ: A Message-Passing View of Post-Training Quantization5h◆$\Psi$-0.6: Adaptive Streams of Thought in a Unified Vision-Language World Model5h◆Not All Information Is Worth Asking For: Decision-Informed Information Seeking with LLMs5h◆Evidence-Grounded SLM Behavioral Prediction Architecture for Future Assistance Use5h◆POSEIDON: Scaling Training Environments for Scientific Agents from Code Repositories5h◆ALLMTS: Automated LLM-based Medical Triage System5h◆When Agents Fail: Model or Harness--Who's to Blame?5h◆LGMT: A Tool for Testing the Logical Reasoning Reliability of LLMs5h◆WiMoT: Replay-Free Continual Wi-Fi Sensing via Moment Transport5h◆Retiming Robot Demonstrations with a Learned Speed Prior5h◆Advancing SVD-based LLM Compression via Layer-Wise Error Model Search5h◆Validating the Comparison, Not Just the Scorer: Why Overall Accuracy Can Mislead in Interactive LLM Evaluation5h◆From Target Selection to Condition Reuse: Auditing Residual Interventions in Tool-Use Models5h◆Distributional Alignment of LLMs and Its Generalization Properties5h◆Collaborative In-Context Learning for Indoor Radio Map Estimation5h◆What Open-Source Projects Tell Their Coding Agents: A Census of AGENTS.md and CLAUDE.md5h◆Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data5h◆
News/ToolGrad: Efficient Tool-use Dataset Generation with Textual "Gradients"
arxiv
PublishedJune 18, 2026 at 4:00 AM
▲bullish

ToolGrad: Efficient Tool-use Dataset Generation with Textual "Gradients"

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

arXiv:2508.04086v3 Announce Type: replace Abstract: Prior work synthesizes tool-use LLM datasets by first generating a user query, followed by complex tool-use annotations like depth-first search (DFS). This leads to inevitable annotation failures and low efficiency in data generation. We introduce

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
    ToolGrad
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#llm#dataset#open-source#efficiency

No replies yet. Be first.

Mentioned models
01
  • 01
    ToolGrad
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#llm#dataset#open-source#efficiency

Related coverage

More from ARXIV
arxivRomanized Arabic Across Dialects: Views, Usage Patterns, and Linguistic Variation5harxivDo AI-for-Science Agents Preserve Model Safety?5harxivBehaviour analysis for large language model-driven agents5harxivMPQ: A Message-Passing View of Post-Training Quantization5h
The Bubble Brief
MON · WED · FRI

Read llm 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