Toolformer: Language Models Can Teach Themselves to Use Tools | Paper Citation Record

Observation 399cf2dd-be5c-4687-98bb-577cfda60a4e · inbound

Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks cites this paper.

Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-12T16:48:28.175749Z

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Observation 8ca72977-b82b-4f9e-9024-f9e940c4fc1d · inbound

ViperGPT: Visual Inference via Python Execution for Reasoning cites this paper.

ViperGPT: Visual Inference via Python Execution for Reasoning Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-05-17T18:15:14.531433Z

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ART: Automatic multi-step reasoning and tool-use for large language models cites this paper.

ART: Automatic multi-step reasoning and tool-use for large language models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 146

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T19:03:06.230853Z

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Reflexion: Language Agents with Verbal Reinforcement Learning cites this paper.

Reflexion: Language Agents with Verbal Reinforcement Learning Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-10T19:57:53.077868Z

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MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action cites this paper.

MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-14T01:17:58.791366Z

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Language Models can Solve Computer Tasks cites this paper.

Language Models can Solve Computer Tasks Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-05-17T12:17:26.799019Z

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HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face cites this paper.

HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-14T00:06:45.557999Z

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CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society cites this paper.

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-05-14T01:40:53.643493Z

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A Survey of Large Language Models cites this paper.

A Survey of Large Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 82

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ChemCrow: Augmenting large-language models with chemistry tools cites this paper.

ChemCrow: Augmenting large-language models with chemistry tools Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-15T19:05:23.087127Z

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API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs cites this paper.

API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T20:51:41.250457Z

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Observation 4d5b17bb-c2e6-4194-9a99-e9ca52e4e9e0 · inbound

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency cites this paper.

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-14T18:36:18.576146Z

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Reasoning with Language Model is Planning with World Model cites this paper.

Reasoning with Language Model is Planning with World Model Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 163

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Gorilla: Large Language Model Connected with Massive APIs cites this paper.

Gorilla: Large Language Model Connected with Massive APIs Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-11T23:22:17.053948Z

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Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory cites this paper.

Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-15T18:37:20.962144Z

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ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models cites this paper.

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-15T18:15:55.778055Z

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Mind2Web: Towards a Generalist Agent for the Web cites this paper.

Mind2Web: Towards a Generalist Agent for the Web Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-15T20:05:16.139915Z

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A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 195

Resolution: verified exact; local_arxiv, observed 2026-05-16T02:56:42.199708Z

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SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models cites this paper.

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:59:45.363322Z

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Cognitive Architectures for Language Agents cites this paper.

Cognitive Architectures for Language Agents Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-05-16T19:33:44.495490Z

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Large Language Models as Optimizers cites this paper.

Large Language Models as Optimizers Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-15T00:04:31.349011Z

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The Rise and Potential of Large Language Model Based Agents: A Survey cites this paper.

The Rise and Potential of Large Language Model Based Agents: A Survey Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 93

Resolution: verified exact; local_arxiv, observed 2026-05-11T10:47:50.405058Z

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The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) cites this paper.

The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 112

Resolution: verified exact; local_arxiv, observed 2026-05-15T23:26:06.564761Z

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ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving cites this paper.

ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-19T09:19:36.168018Z

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DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines cites this paper.

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-05-11T18:57:47.027373Z

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MemGPT: Towards LLMs as Operating Systems cites this paper.

MemGPT: Towards LLMs as Operating Systems Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-10T19:57:53.077868Z

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Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection cites this paper.

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 149

Resolution: metadata mismatch; local_arxiv, observed 2026-05-12T14:15:11.196775Z

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GAIA: a benchmark for General AI Assistants cites this paper.

GAIA: a benchmark for General AI Assistants Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 63

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GAIA: a benchmark for General AI Assistants cites this paper.

GAIA: a benchmark for General AI Assistants Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 191

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Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations cites this paper.

Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 8

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SGLang: Efficient Execution of Structured Language Model Programs cites this paper.

SGLang: Efficient Execution of Structured Language Model Programs Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 41

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Retrieval-Augmented Generation for Large Language Models: A Survey cites this paper.

Retrieval-Augmented Generation for Large Language Models: A Survey Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 108

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RepairAgent: An Autonomous, LLM-Based Agent for Program Repair cites this paper.

RepairAgent: An Autonomous, LLM-Based Agent for Program Repair Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 28

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InternLM2 Technical Report cites this paper.

InternLM2 Technical Report Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 196

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LLM Agents can Autonomously Exploit One-day Vulnerabilities cites this paper.

LLM Agents can Autonomously Exploit One-day Vulnerabilities Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 15

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A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 125

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$\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains cites this paper.

$\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 18

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Learning to Ask: When LLM Agents Meet Unclear Instruction cites this paper.

Learning to Ask: When LLM Agents Meet Unclear Instruction Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 22

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Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models cites this paper.

Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 62

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OS-ATLAS: A Foundation Action Model for Generalist GUI Agents cites this paper.

OS-ATLAS: A Foundation Action Model for Generalist GUI Agents Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 85

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Lies, Damned Lies, and Distributional Language Statistics: Persuasion and Deception with Large Language Models cites this paper.

Lies, Damned Lies, and Distributional Language Statistics: Persuasion and Deception with Large Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 2023

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IGC: Integrating a Gated Calculator into an LLM to Solve Arithmetic Tasks Reliably and Efficiently cites this paper.

IGC: Integrating a Gated Calculator into an LLM to Solve Arithmetic Tasks Reliably and Efficiently Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 25

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Large Language Model Interface for Home Energy Management Systems cites this paper.

Large Language Model Interface for Home Energy Management Systems Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 18

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AgentRec: Agent Recommendation Using Sentence Embeddings Aligned to Human Feedback cites this paper.

AgentRec: Agent Recommendation Using Sentence Embeddings Aligned to Human Feedback Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 21

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Locality-aware Fair Scheduling in LLM Serving cites this paper.

Locality-aware Fair Scheduling in LLM Serving Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 40

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DBRouting: Routing End User Queries to Databases for Answerability cites this paper.

DBRouting: Routing End User Queries to Databases for Answerability Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 13

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PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback cites this paper.

PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 19

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MDCrow: Automating Molecular Dynamics Workflows with Large Language Models cites this paper.

MDCrow: Automating Molecular Dynamics Workflows with Large Language Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 33

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Process Reward Models for LLM Agents: Practical Framework and Directions cites this paper.

Process Reward Models for LLM Agents: Practical Framework and Directions Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 47

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LA-RCS: LLM-Agent-Based Robot Control System cites this paper.

LA-RCS: LLM-Agent-Based Robot Control System Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 22

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Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control cites this paper.

Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 16

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InFact: Informativeness Alignment for Improved LLM Factuality cites this paper.

InFact: Informativeness Alignment for Improved LLM Factuality Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 39

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Who Reasons in the Large Language Models? cites this paper.

Who Reasons in the Large Language Models? Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 35

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Climate Finance Bench Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 35

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Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration cites this paper.

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MedOrchestra: A Hybrid Cloud-Local LLM Approach for Clinical Data Interpretation cites this paper.

MedOrchestra: A Hybrid Cloud-Local LLM Approach for Clinical Data Interpretation Toolformer: Language Models Can Teach Themselves to Use Tools

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SentinelAgent: Graph-based Anomaly Detection in Multi-Agent Systems cites this paper.

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Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering cites this paper.

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Self-Challenging Language Model Agents cites this paper.

Self-Challenging Language Model Agents Toolformer: Language Models Can Teach Themselves to Use Tools

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Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 31

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Question Answering under Temporal Conflict: Evaluating and Organizing Evolving Knowledge with LLMs cites this paper.

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CoRT: Code-integrated Reasoning within Thinking cites this paper.

CoRT: Code-integrated Reasoning within Thinking Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 54

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OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems cites this paper.

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems Toolformer: Language Models Can Teach Themselves to Use Tools

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Build the web for agents, not agents for the web Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 51

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TableVault: Managing Dynamic Data Collections for LLM-Augmented Workflows cites this paper.

TableVault: Managing Dynamic Data Collections for LLM-Augmented Workflows Toolformer: Language Models Can Teach Themselves to Use Tools

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QuickSilver -- Speeding up LLM Inference through Dynamic Token Halting, KV Skipping, Contextual Token Fusion, and Adaptive Matryoshka Quantization cites this paper.

QuickSilver -- Speeding up LLM Inference through Dynamic Token Halting, KV Skipping, Contextual Token Fusion, and Adaptive Matryoshka Quantization Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 2022

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Observation e239d725-439b-4201-b553-124d61afaf36 · inbound

Learning Adapter Rank via Symmetry Breaking cites this paper.

Learning Adapter Rank via Symmetry Breaking Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 1

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Observation ddb17d27-535d-41e0-9462-2883dd5cd10f · inbound

DICE-BENCH: Evaluating the Tool-Use Capabilities of Large Language Models in Multi-Round, Multi-Party Dialogues cites this paper.

DICE-BENCH: Evaluating the Tool-Use Capabilities of Large Language Models in Multi-Round, Multi-Party Dialogues Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 36

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Observation bf6b6ce2-0d5c-4806-9457-aca430d98030 · inbound

LineRetriever: Planning-Aware Observation Reduction for Web Agents cites this paper.

LineRetriever: Planning-Aware Observation Reduction for Web Agents Toolformer: Language Models Can Teach Themselves to Use Tools

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Observation ea3df4ac-9fa5-4d50-b165-978d2dfe9784 · inbound

PresentAgent: Multimodal Agent for Presentation Video Generation cites this paper.

PresentAgent: Multimodal Agent for Presentation Video Generation Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 25

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Replacing thinking with tool usage enables reasoning in small language models cites this paper.

Replacing thinking with tool usage enables reasoning in small language models Toolformer: Language Models Can Teach Themselves to Use Tools

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Observation 2c37d754-62b6-454a-9720-5db83994c445 · inbound

Automating MD simulations for Proteins using Large language Models: NAMD-Agent cites this paper.

Automating MD simulations for Proteins using Large language Models: NAMD-Agent Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 36

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Observation c2f73b29-0798-4f11-b579-820a2949b1d0 · inbound

Integrating External Tools with Large Language Models to Improve Accuracy cites this paper.

Integrating External Tools with Large Language Models to Improve Accuracy Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 16

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Observation c91362e9-c695-4a5b-bfbe-18c89e2c1be0 · inbound

eSapiens: A Platform for Secure and Auditable Retrieval-Augmented Generation cites this paper.

eSapiens: A Platform for Secure and Auditable Retrieval-Augmented Generation Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:58:33.830900Z

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From Multi-Agent Systems and the Semantic Web to Agentic AI: A Unified Narrative of the Web of Agents cites this paper.

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Reference 85

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Observation 15b7b6c7-8e84-4df7-a904-398435224e19 · inbound

A Simple "Try Again" Can Elicit Multi-Turn LLM Reasoning cites this paper.

A Simple "Try Again" Can Elicit Multi-Turn LLM Reasoning Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 50

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Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems cites this paper.

Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 41

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Observation 8d5eaac3-0a94-4a1f-9d98-41cd4031204d · inbound

eSapiens's DEREK Module: Deep Extraction & Reasoning Engine for Knowledge with LLMs cites this paper.

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Reference 10

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Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback cites this paper.

Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 31

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OneShield -- the Next Generation of LLM Guardrails cites this paper.

OneShield -- the Next Generation of LLM Guardrails Toolformer: Language Models Can Teach Themselves to Use Tools

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Augmented Vision-Language Models: A Systematic Review cites this paper.

Augmented Vision-Language Models: A Systematic Review Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 96

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ProbGuard: Proactive Runtime Monitoring for LLM Agent Safety via Probabilistic Prediction cites this paper.

ProbGuard: Proactive Runtime Monitoring for LLM Agent Safety via Probabilistic Prediction Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 39

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AgREE: Agentic Reasoning for Knowledge Graph Completion on Emerging Entities cites this paper.

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Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

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Reference 118

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FlexNGIA 2.0: Redesigning the Internet with Agentic AI -- Protocols, Services, and Traffic Engineering Designed, Deployed, and Managed by AI cites this paper.

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UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning cites this paper.

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Reference 55

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Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator cites this paper.

Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator Toolformer: Language Models Can Teach Themselves to Use Tools

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Observation 3fd5ca50-a0c3-44bb-949e-599c65241b9c · inbound

Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator cites this paper.

Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator Toolformer: Language Models Can Teach Themselves to Use Tools

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Observation f4bd0a90-9c58-4eb8-8063-ffd74baff6cb · inbound

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data cites this paper.

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 30

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Estimating the Empowerment of Language Model Agents cites this paper.

Estimating the Empowerment of Language Model Agents Toolformer: Language Models Can Teach Themselves to Use Tools

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Explore-Execute Chain: Towards an Efficient Structured Reasoning Paradigm cites this paper.

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MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding cites this paper.

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Observation 3515a5dc-6e05-432e-874f-989fa6dc9172 · inbound

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety cites this paper.

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Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism cites this paper.

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Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-18T03:05:48.109683Z

Source-reported events for the cited work

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Observation 0ac8b1e5-4ae2-4726-904f-82969c38c322 · inbound

A Benchmark for Omni-Modal Reasoning in Long Videos cites this paper.

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Architecting Agentic Communities using Design Patterns cites this paper.

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LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems cites this paper.

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Reference 133

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Observation c111b749-6393-46fb-ba24-f3d230ec7ac6 · inbound

BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning cites this paper.

BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning Toolformer: Language Models Can Teach Themselves to Use Tools

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Coverage vector

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Outbound references

Pith citing papers