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ProgAgent framework enhances LLM tool orchestration via programmatic training

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced ProgAgent, a new training framework designed to improve how large language models (LLMs) orchestrate tools for complex, long-horizon tasks. Unlike traditional Direct Tool Calling (DTC) methods that can suffer from context rot, ProgAgent utilizes Programmatic Tool Calling (PTC) by invoking tools through executable code and managing intermediate results in runtime variables. This approach, trained on a synthesized set of tasks, has demonstrated higher success rates compared to baseline models, notably achieving a 30.7% pass rate on LOCA-bench where other models scored zero. AI

IMPACT This research could lead to more capable LLM agents that can handle complex, multi-step tasks more reliably.

RANK_REASON The cluster describes a new research paper detailing a novel training framework for LLMs.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

ProgAgent framework enhances LLM tool orchestration via programmatic training

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The cluster describes a new research paper detailing a novel training framework for LLMs.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Hao Li, Keqing He, Longtao Zheng, Junlong Li, Weihao Zeng, Qian Liu, Yuzhen Huang ·

    ProgAgent: Learning Tool Orchestration through Programmatic Training

    arXiv:2610.14774v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly expected to orchestrate diverse tools over long-horizon tasks. Existing agents typically use Direct Tool Calling (DTC), where the model invokes tools sequentially, and tool responses acc…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    ProgAgent: Learning Tool Orchestration through Programmatic Training

    Large language models (LLMs) are increasingly expected to orchestrate diverse tools over long-horizon tasks. Existing agents typically use Direct Tool Calling (DTC), where the model invokes tools sequentially, and tool responses accumulate in the model context, which can lead to …

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