Saved in:
| Main Authors: | Chen, Edwin, Bibi, Zulekha |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.14295 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ML-Tool-Bench: Tool-Augmented Planning for ML Tasks
by: Chittepu, Yaswanth, et al.
Published: (2025)
by: Chittepu, Yaswanth, et al.
Published: (2025)
ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
by: Liu, Zexi, et al.
Published: (2025)
by: Liu, Zexi, et al.
Published: (2025)
SynthTools: A Framework for Scaling Synthetic Tools for Agent Development
by: Castellani, Tommaso, et al.
Published: (2025)
by: Castellani, Tommaso, et al.
Published: (2025)
A Survey on Data Quality Dimensions and Tools for Machine Learning
by: Zhou, Yuhan, et al.
Published: (2024)
by: Zhou, Yuhan, et al.
Published: (2024)
LLM Agents Making Agent Tools
by: Wölflein, Georg, et al.
Published: (2025)
by: Wölflein, Georg, et al.
Published: (2025)
Incentivizing Agentic Reasoning in LLM Judges via Tool-Integrated Reinforcement Learning
by: Xu, Ran, et al.
Published: (2025)
by: Xu, Ran, et al.
Published: (2025)
Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
by: Thaman, Kunvar
Published: (2026)
by: Thaman, Kunvar
Published: (2026)
Understanding Tool-Integrated Reasoning
by: Lin, Heng, et al.
Published: (2025)
by: Lin, Heng, et al.
Published: (2025)
Tool-Star: Empowering LLM-Brained Multi-Tool Reasoner via Reinforcement Learning
by: Dong, Guanting, et al.
Published: (2025)
by: Dong, Guanting, et al.
Published: (2025)
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
by: Shen, ChengAo, et al.
Published: (2024)
by: Shen, ChengAo, et al.
Published: (2024)
PLAY2PROMPT: Zero-shot Tool Instruction Optimization for LLM Agents via Tool Play
by: Fang, Wei, et al.
Published: (2025)
by: Fang, Wei, et al.
Published: (2025)
The Causal Impact of Tool Affordance on Safety Alignment in LLM Agents
by: Yu, Shasha, et al.
Published: (2026)
by: Yu, Shasha, et al.
Published: (2026)
WALT: Web Agents that Learn Tools
by: Prabhu, Viraj, et al.
Published: (2025)
by: Prabhu, Viraj, et al.
Published: (2025)
RLFactory: A Plug-and-Play Reinforcement Learning Post-Training Framework for LLM Multi-Turn Tool-Use
by: Chai, Jiajun, et al.
Published: (2025)
by: Chai, Jiajun, et al.
Published: (2025)
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
by: Trirat, Patara, et al.
Published: (2024)
by: Trirat, Patara, et al.
Published: (2024)
Tool Learning with Foundation Models
by: Qin, Yujia, et al.
Published: (2023)
by: Qin, Yujia, et al.
Published: (2023)
Data Pipeline Training: Integrating AutoML to Optimize the Data Flow of Machine Learning Models
by: Wu, Jiang, et al.
Published: (2024)
by: Wu, Jiang, et al.
Published: (2024)
ToolRL: Reward is All Tool Learning Needs
by: Qian, Cheng, et al.
Published: (2025)
by: Qian, Cheng, et al.
Published: (2025)
Tool-as-Interface: Learning Robot Policies from Observing Human Tool Use
by: Chen, Haonan, et al.
Published: (2025)
by: Chen, Haonan, et al.
Published: (2025)
Outcome-Aware Tool Selection for Semantic Routers: Latency-Constrained Learning Without LLM Inference
by: Chen, Huamin, et al.
Published: (2026)
by: Chen, Huamin, et al.
Published: (2026)
TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
by: Gao, Shanghua, et al.
Published: (2025)
by: Gao, Shanghua, et al.
Published: (2025)
Current Agents Fail to Leverage World Model as Tool for Foresight
by: Qian, Cheng, et al.
Published: (2026)
by: Qian, Cheng, et al.
Published: (2026)
Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)
by: Knorr, Marius S., et al.
Published: (2026)
by: Knorr, Marius S., et al.
Published: (2026)
How Many Tools Should an LLM Agent See? A Chance-Corrected Answer
by: Repantis, Vyzantinos, et al.
Published: (2026)
by: Repantis, Vyzantinos, et al.
Published: (2026)
AutoML-Med: A Framework for Automated Machine Learning in Medical Tabular Data
by: Francia, Riccardo, et al.
Published: (2025)
by: Francia, Riccardo, et al.
Published: (2025)
LoopTool: Closing the Data-Training Loop for Robust LLM Tool Calls
by: Zhang, Kangning, et al.
Published: (2025)
by: Zhang, Kangning, et al.
Published: (2025)
When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs
by: Zeng, Yifan, et al.
Published: (2026)
by: Zeng, Yifan, et al.
Published: (2026)
Provable Benefits of In-Tool Learning for Large Language Models
by: Houliston, Sam, et al.
Published: (2025)
by: Houliston, Sam, et al.
Published: (2025)
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey
by: Gu, Yang, et al.
Published: (2024)
by: Gu, Yang, et al.
Published: (2024)
ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities
by: Lu, Jiarui, et al.
Published: (2024)
by: Lu, Jiarui, et al.
Published: (2024)
CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning
by: Wu, Duo, et al.
Published: (2024)
by: Wu, Duo, et al.
Published: (2024)
PALADIN: Self-Correcting Language Model Agents to Cure Tool-Failure Cases
by: Vuddanti, Sri Vatsa, et al.
Published: (2025)
by: Vuddanti, Sri Vatsa, et al.
Published: (2025)
Recoverability Has a Law: The ERR Measure for Tool-Augmented Agents
by: Vuddanti, Sri Vatsa, et al.
Published: (2026)
by: Vuddanti, Sri Vatsa, et al.
Published: (2026)
ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool Learning
by: Zeng, Xingshan, et al.
Published: (2025)
by: Zeng, Xingshan, et al.
Published: (2025)
Many-to-English Machine Translation Tools, Data, and Pretrained Models
by: Gowda, Thamme, et al.
Published: (2021)
by: Gowda, Thamme, et al.
Published: (2021)
TAACKIT: Track Annotation and Analytics with Continuous Knowledge Integration Tool
by: Lee, Lily, et al.
Published: (2024)
by: Lee, Lily, et al.
Published: (2024)
EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis
by: Song, Xiaoshuai, et al.
Published: (2026)
by: Song, Xiaoshuai, et al.
Published: (2026)
rule4ml: An Open-Source Tool for Resource Utilization and Latency Estimation for ML Models on FPGA
by: Rahimifar, Mohammad Mehdi, et al.
Published: (2024)
by: Rahimifar, Mohammad Mehdi, et al.
Published: (2024)
SMART: Self-Aware Agent for Tool Overuse Mitigation
by: Qian, Cheng, et al.
Published: (2025)
by: Qian, Cheng, et al.
Published: (2025)
A Comprehensive Perspective on Explainable AI across the Machine Learning Workflow
by: Paterakis, George, et al.
Published: (2025)
by: Paterakis, George, et al.
Published: (2025)
Similar Items
-
ML-Tool-Bench: Tool-Augmented Planning for ML Tasks
by: Chittepu, Yaswanth, et al.
Published: (2025) -
ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
by: Liu, Zexi, et al.
Published: (2025) -
SynthTools: A Framework for Scaling Synthetic Tools for Agent Development
by: Castellani, Tommaso, et al.
Published: (2025) -
A Survey on Data Quality Dimensions and Tools for Machine Learning
by: Zhou, Yuhan, et al.
Published: (2024) -
LLM Agents Making Agent Tools
by: Wölflein, Georg, et al.
Published: (2025)