mlsanityData to 14 Oct 2026

ToolRerank: Adaptive and Hierarchy-Aware Reranking for Tool Retrieval

arXiv 2403.06551 ↗First posted 11 Mar 2024cs.IRcited by 41

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Cited by 24 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Tool learning aims to extend the capabilities of large language models (LLMs) with external tools. A major challenge in tool learning is how to support a large number of tools, including unseen tools. To address this challenge, previous studies have proposed retrieving suitable tools for the LLM based on the user query. However, previously proposed methods do not consider the differences between seen and unseen tools, nor do they take the hierarchy of the tool library into account, which may lead to suboptimal performance for tool retrieval. Therefore, to address the aforementioned issues, we propose ToolRerank, an adaptive and hierarchy-aware reranking method for tool retrieval to further refine the retrieval results. Specifically, our proposed ToolRerank includes Adaptive Truncation, which truncates the retrieval results related to seen and unseen tools at different positions, and Hierarchy-Aware Reranking, which makes retrieval results more concentrated for single-tool queries and more diverse for multi-tool queries. Experimental results show that ToolRerank can improve the quality of the retrieval results, leading to better execution results generated by the LLM.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Mar 2024.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 12; 2026: 23.

41 papers.

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  1. 2024Tool Learning with Large Language Models: A Surveycited by 223
  2. 2025Prompt Injection Attack to Tool Selection in LLM Agentscited by 158
  3. 2026SkillRouter: Skill Routing for LLM Agents at Scalecited by 61
  4. 2025MCP-Zero: Active Tool Discovery for Autonomous LLM Agentscited by 33
  5. 2025Retrieval-Augmented Generation: A Comprehensive Survey of Architectures, Enhancements, and Robustness Frontierscited by 27
  6. 2024Towards Completeness-Oriented Tool Retrieval for Large Language Modelscited by 26
  7. 2024StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement Learningcited by 25
  8. 2026ReCreate: Reasoning and Creating Domain Agents Driven by Experiencecited by 24
  9. 2024Toolshed: Scale Tool-Equipped Agents with Advanced RAG-Tool Fusion and Tool Knowledge Basescited by 23
  10. 2024Efficient and Scalable Estimation of Tool Representations in Vector Spacecited by 22
  11. 2025MemTool: Optimizing Short-Term Memory Management for Dynamic Tool Calling in LLM Agent Multi-Turn Conversationscited by 21
  12. 2026Don't Break the Cache: An Evaluation of Prompt Caching for Long-Horizon Agentic Taskscited by 19
29 more
  1. 2025LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queriescited by 17
  2. 2026From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skillscited by 16
  3. 2025Tool-to-Agent Retrieval: Bridging Tools and Agents for Scalable LLM Multi-Agent Systemscited by 15
  4. 2025SOP-Agent: Empower General Purpose AI Agent with Domain-Specific SOPscited by 11
  5. 2026How Many Tools Should an LLM Agent See? A Chance-Corrected Answercited by 7
  6. 2025Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Buildercited by 4
  7. 2025Putting on the Thinking Hats: A Survey on Chain of Thought Fine-tuning from the Perspective of Human Reasoning Mechanismcited by 4
  8. 2026JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agentscited by 4
  9. 2026Right Family, Wrong Skill: Evaluating Risk Exposure in Agent Skill Retrievalcited by 4
  10. 2026PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Modelscited by 4
  11. 2024Task-Aligned Tool Recommendation for Large Language Modelscited by 3
  12. 2025GATE: Graph-based Adaptive Tool Evolution Across Diverse Taskscited by 3
  13. 2025Schema as Parameterized Tools for Universal Information Extractioncited by 3
  14. 2025MassTool: A Multi-Task Search-Based Tool Retrieval Framework for Large Language Modelscited by 3
  15. 2026FinToolSyn: A forward synthesis Framework for Financial Tool-Use Dialogue Data with Dynamic Tool Retrievalcited by 3
  16. 2026Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Predictioncited by 3
  17. 2026TabAgent: A Framework for Replacing Agentic Generative Components with Tabular-Textual Classifierscited by 2
  18. 2026Tool Retrieval Bridge: Aligning Vague Instructions with Retriever Preferences via Bridge Modelcited by 2
  19. 2026IEA: Amateur-Friendly Conversational Image Editing Agent via Three Stages of Multitask Alignmentcited by 2
  20. 2026When Tool-Backed Skill Retrieval Fails: Source-Style Collapse in Executable Capability Retrievalcited by 2
  21. 2026Risk-Aware Reranking for Agentic Tool Retrievalcited by 2
  22. 2026Outcome-Aware Tool Selection for Semantic Routers: Latency-Constrained Learning Without LLM Inferencecited by 1
  23. 2026AgentSearchBench: A Benchmark for AI Agent Search in the Wildcited by 1
  24. 2026SE-GoS: Self-Evolving Graph-of-Skills for Skill Library at Scalecited by 1
  25. 2026GraphSkillAA: Attribution-Guided Skill-Graph Updating with Targeted Validation and Rollbackcited by 1
  26. 2026FitText: Evolving Agent Tool Ecologies via Memetic Retrievalcited by 0
  27. 2026W-RAG: Source-Aware Retrieval for Enterprise Document Generation from Heterogeneous Knowledge Basescited by 0
  28. 2026Self-Evolving Agents via Likelihood-Guided Tool-Space Optimizationcited by 0
  29. 2026From Relevance to Validity: Zero-Shot Tool Selection via Functional and Contextual Validationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Data-Efficient Massive Tool Retrieval: A Reinforcement Learning Approach for Query-Tool Alignment with Language Models
  2. 2024Enhancing Tool Retrieval with Iterative Feedback from Large Language Models
  3. 2025Retrieval Models Aren't Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models
  4. 2025Tools are under-documented: Simple Document Expansion Boosts Tool Retrieval
  5. 2025ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers
  6. 2024Toolken+: Improving LLM Tool Usage with Reranking and a Reject Option
  7. 2024Planning and Editing What You Retrieve for Enhanced Tool Learning
  8. 2026Semantic Tool Discovery for Large Language Models: A Vector-Based Approach to MCP Tool Selection