tool calling
PulseAugur coverage of tool calling — every cluster mentioning tool calling across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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LLM agents slash token use with new 'Code Mode' approach
A new approach called "Code Mode" aims to significantly reduce the number of tokens required by large language models when interacting with multiple tools. Instead of serializing all tool definitions and intermediate re…
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Liquid AI releases 2.6B model capable of 128K context on phones
Liquid AI has released LFM2.5-2.6B, a compact language model designed for local AI applications. Despite its small size of 2.69 billion parameters, the model boasts a 128K context window and supports tool calling, makin…
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Google's A2A protocol finds niche in agent-to-agent communication
Google's Agent2Agent (A2A) protocol, introduced in April 2025, aims to standardize communication between independent AI agents from various vendors and frameworks. Initially met with skepticism due to market saturation …
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New RL methods enhance LLM training stability and efficiency · 7 sources tracked
Researchers have developed several new methods to improve the stability and efficiency of reinforcement learning (RL) in large language models (LLMs). STARE addresses policy entropy collapse by reweighting token-level a…
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AI terms like Agents and RAG are reshaping careers, demanding new knowledge
This article discusses the growing prevalence of AI terms like AI Agents, Automation, Tool Calling, RAG, and Multi-Agent Systems. It suggests that understanding these concepts is crucial for career preservation in the f…
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Microsoft details its Agent Framework for building AI applications
Microsoft has released the third part of its "Agent Framework – Building Blocks for AI" series on the .NET blog. This installment delves into the creation of AI agents, focusing on essential components for their develop…