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RT by @_akhaliq: Agentic ESOpt: fine-tuning long-horizon LLM agents with minimal GPU memory This…

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Merged summary

TL;DR - Agentic ESOpt is a framework for fine-tuning long-horizon LLM agents using evolution strategies rather than backpropagation. It enables full-parameter optimization at inference-level GPU memory and reports strong improvements on WebArena-Lite and other unspecified evaluations.

  • Replaces gradient-based backpropagation with evolution-strategy optimization.
  • Reduces training memory requirements to approximately those of inference.
  • Supports full-parameter optimization rather than limiting updates to a small adapter.
  • Targets long-horizon agent tasks and reports gains on WebArena-Lite.

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RT by @_akhaliq: Agentic ESOpt: fine-tuning long-horizon LLM agents with minimal GPU memory This…

@HuggingPapers 2026-08-19
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Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-19 14:26:09.657076 UTC

TL;DR - Agentic ESOpt is a framework for fine-tuning long-horizon LLM agents using evolution strategies rather than backpropagation. It enables full-parameter optimization at inference-level GPU memory and reports strong improvements on WebArena-Lite and other unspecified evaluations.

  • Replaces gradient-based backpropagation with evolution-strategy optimization.
  • Reduces training memory requirements to approximately those of inference.
  • Supports full-parameter optimization rather than limiting updates to a small adapter.
  • Targets long-horizon agent tasks and reports gains on WebArena-Lite.
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