Function Calling - Edgentiq

MCP-Flow: Automating LLM Agent Tool Use in Dynamic Environments

FunReason-MT: Enhancing AI’s Ability to Use Tools in Complex Conversations

Advancing AI Agents: A Framework for Synthetic Data Generation

Enhancing LLM Agent Reliability: A Fine-Grained Approach to Function Calling

Small Language Models: The Smart Choice for Agentic AI Systems

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Evaluating LLM Precision: A New Benchmark for Function Calling Instruction Adherence

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Unpacking Function Calling’s Influence on Large Language Model Behavior

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Guiding Language Models for Better Tool Use and Clearer Decisions

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Evaluating AI Agent Architectures for Enterprise Workflows

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VehicleWorld: Advancing AI Interaction in Smart Car Cockpits

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Improving AI Agent Dialogue and Tool Use in Role-Playing Scenarios

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Benchmarking AI Agents: A New Standard for Evaluating Tool Use Capabilities

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Enhancing LLM Function Calling with FunRL: A New Reinforcement Learning Approach

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Simplifying LLM Tool Integration with a Unified, Protocol-Agnostic Approach

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ToolRegistry: Simplifying External Tool Integration for Large Language Models

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Accelerating LLM Function Calling: A Data-Driven Approach to Reduce Latency

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LLM Agents: Unpacking the Architectural Roots of Security Vulnerabilities

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Gen AI News and Updates

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MCP-Flow: Automating LLM Agent Tool Use in Dynamic Environments

October 29, 2025

FunReason-MT: Enhancing AI’s Ability to Use Tools in Complex Conversations

October 29, 2025

Advancing AI Agents: A Framework for Synthetic Data Generation

October 22, 2025