arXiv Machine Learning

When Tool-Backed Skill Retrieval Fails: Source-Style Collapse in Executable Capability Retrieval

arXiv:2608. 16502v1 Announce Type: new Abstract: Large-scale agents increasingly rely on retrieval to access external capabilities.

arXiv AI

Jul 3

ContextNest: Verifiable Context Governance for Autonomous AI Agent

arXiv:2607. 02116v1 Announce Type: new Abstract: Autonomous AI agents increasingly depend on external knowledge stores, yet most retrieval pipelines provide relevance without durable guarantees of provenance, version identity, integrity, traceability, or point-in-time reconstruction.

By Misha Sulpovar (PromptOwl, LLC), Benn R. Konsynski (Goizueta Business School, Emory University), Qaish Kanchwala (IBM Research), Gabe Goodhart (IBM Research)

rag agents

arXiv AI

6d ago

VAKRA: Evaluating Multi-Hop Reasoning Across APIs and Retrieval Under Tool-Use Policies

arXiv:2608. 12282v1 Announce Type: new Abstract: Agents deployed in enterprise settings must reason across structured APIs and document collections, yet existing benchmarks evaluate these capabilities in isolation.

By Ankita Rajaram Naik, Anupama Murthi, Benjamin Elder, Siyu Huo, Raavi Gupta, Abhinav Jain, Praveen Venkateswaran, Abdulhamid Adebayo, Danish Contractor

agents benchmarks

arXiv AI

Jun 12

ToolSense: A Diagnostic Framework for Auditing Parametric Tool Knowledge in LLMs

arXiv:2606. 12451v1 Announce Type: new Abstract: Large language models deployed as agents over large tool catalogs face a critical tool-retrieval bottleneck.

By Ashutosh Hathidara, Sai Shruthi Sistla, Sebastian Schreiber, Sahil Bansal

llms rag agents fine-tuning benchmarks

arXiv AI

Jun 17

Scaling Enterprise Agent Routing: Degradation, Diagnosis, and Recovery

arXiv:2606. 17519v1 Announce Type: cross Abstract: Production LLM assistants route user requests to growing libraries of specialized tools, but how does routing accuracy degrade as the catalog scales?

By Kellen Gillespie, Robyn Perry

llms rag agents

arXiv AI

Jul 29

Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction

arXiv:2607. 25718v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks.

By Xinyi Hong, Pinjun Dong, Xinyang Yu, Binyan Jiang

llms agents benchmarks

arXiv AI

Jun 12

Evoflux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents

arXiv:2606. 12674v1 Announce Type: new Abstract: Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents.

By Kushal Raj Bhandari, Ling Yue, Ching-Yun Ko, Dhaval Patel, Shaowu Pan, Pin-Yu Chen, Jianxi Gao

llms agents reinforcement-learning fine-tuning efficiency

arXiv AI

Aug 7

SkillTrace: Multi-Trace Provenance Auditing for LLM-Agent Skill Reuse

arXiv:2608. 05204v1 Announce Type: new Abstract: LLM-agent ecosystems are rapidly growing around reusable skills: mixed-modality packages of metadata, natural-language instructions, code, tools, references, and operational workflows.

By Jialuo Chen, Minghe Wang, Lingqi Jiang, Jianan Ma, Xinhao Deng, Xiaohu Du, Ruixiao Lin, Yunhao Feng, Linkang Du, Jingyi Wang

llms agents

arXiv Machine Learning

Jul 21

SkillRouter: Skill Routing for LLM Agents at Scale

arXiv:2603. 22455v5 Announce Type: replace Abstract: Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks.

By YanZhao Zheng, ZhenTao Zhang, Chao Ma, YuanQiang Yu, JiHuai Zhu, Yong Wu, Tianze Xu, Baohua Dong, Hangcheng Zhu, Ruohui Huang, Gang Yu

llms rag agents benchmarks

arXiv AI

Jul 3

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair

arXiv:2607. 01916v1 Announce Type: new Abstract: Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long terminal outputs where useful evidence is mixed with irrelevant code and logs.

By Chiwang Luk, Matin Mohammad Najafi, Zhifeng Jia, Wei Yang, Xiuchang Li, Jinwei Zhu, Yang Ren, Lei Chen, Gao Cong

llms agents

arXiv AI

Jul 22

AI Tool Discovery at Scale: All You Need is DNS

arXiv:2607. 18242v1 Announce Type: new Abstract: The coming era of autonomous AI agents demands a discovery mechanism capable of navigating millions of tools, yet existing solutions buckle under O(N) complexity and centralized governance.

By Enhao Chen, Yulin Shao

rag agents efficiency benchmarks

arXiv Machine Learning

Jul 14

ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory

arXiv:2607. 11126v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external tools served by shared providers and accessed by heterogeneous downstream agents.

By Yue Fang, Zhibang Yang, Fangkai Yang, Xiaoting Qin, Liqun Li, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang

llms agents benchmarks

arXiv AI

Jun 3

Diagnosing Knowledge Gaps in LLM Tool Use: An Agentic Benchmark for Novel API Acquisition

arXiv:2606. 03657v1 Announce Type: new Abstract: Large language models for code generation often need to use APIs that are absent from their pretraining data.

By Jinnuo Liu, Yue Peng, Jinhan Niu, Hongyi Wen

llms agents fine-tuning benchmarks

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