arXiv AI
Aug 11
ToolUniverse: An open platform for democratizing AI scientists
arXiv:2509. 23426v3 Announce Type: replace Abstract: AI scientists are emerging computational systems that serve as collaborative partners in discovery.
Open, Reliable, and Collective: A Community-Driven Framework for Tool-Using AI Agents
arXiv:2604. 00137v2 Announce Type: replace Abstract: Tool-integrated LLMs retrieve information, perform computations, and take real-world actions, but their reliability depends on both tool-use accuracy and intrinsic tool accuracy, including tool correctness, stability, and safety.
Related stories
Hugging Face Blog
Feb 12
OpenEnv in Practice: Evaluating Tool-Using Agents in Real-World Environments
arXiv AI
Jun 12
AgentBeats: Agentifying Agent Assessment for Openness, Standardization, and Reproducibility
arXiv:2606. 13608v1 Announce Type: new Abstract: Agent systems are advancing quickly across domains, but their evaluation remains fragmented.
Hugging Face Trending Papers
Jul 15
AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities
As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical. However, current evaluation pipelines remain highly fragmented and tightly coupled, hindering reproducibility and causing redundant engineering.
arXiv AI
Jul 16
AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities
arXiv:2607. 13705v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical.
arXiv AI
Jul 17
Copy-on-Write Scoring: Application-Specific Agent Evaluations
arXiv:2607. 14336v1 Announce Type: cross Abstract: Trustworthy deployment of LLM-based agents in software systems requires evaluating how they perform on application-specific workflows, with enough granularity to localize where they succeed and fail.
arXiv AI
Sep 1
AgenTRIM: Tool Risk Mitigation for Agentic AI
arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper t...
arXiv AI
Jun 9
WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces
arXiv:2606. 09426v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly operate in runtimes that combine visual desktop control, command-line execution, code editing, browsers, and external tools.
arXiv AI
Jun 11
Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessment
arXiv:2606. 11672v1 Announce Type: cross Abstract: This paper explores the value of agentic AI tools for cybersecurity purposes.
arXiv AI
Sep 10
Agents Trust Tools Too Much: Measuring Reliance on Unreliable Tools
arXiv:2609.05587v1 Announce Type: new Abstract: Existing evaluations of tool-using agents primarily measure whether an agent can successfully complete diverse tasks with tools. These evaluations gene...
arXiv AI
Sep 10
DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents
arXiv:2609.06059v1 Announce Type: new Abstract: As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to a...
arXiv AI
Aug 3
Tool Specifications Matter: Uncovering and Mitigating Safety Risks in AI Agents
arXiv:2607. 29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential real-world actions.