EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses
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TL;DR - EvoUndo is a framework for verifying whether runtime self-modifications made by LLM agents can be safely reversed across counterfactual states. Its results show that reliable recovery depends on precise state grounding and sufficiently expressive recovery mechanisms, not iterative prompting alone.
- Among 600 unseen self-evolution tasks, 197 capability-improving mutations failed recoverability verification.
- Conventional repair strategies recovered none of the 197 failures under the original recovery representation; deterministic oracle analysis recovered 48.
- Exact state-address grounding recovered 38/48 cases when the original recovery language was sufficient.
- Extending the recovery calculus raised oracle recovery to 191/197 and enabled recovery on 142/143 failures attributed to insufficient language expressivity.
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EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses
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Hugging Face upvotes 9
TL;DR - EvoUndo is a framework for verifying whether runtime self-modifications made by LLM agents can be safely reversed across counterfactual states. Its results show that reliable recovery depends on precise state grounding and sufficiently expressive recovery mechanisms, not iterative prompting alone.
- Among 600 unseen self-evolution tasks, 197 capability-improving mutations failed recoverability verification.
- Conventional repair strategies recovered none of the 197 failures under the original recovery representation; deterministic oracle analysis recovered 48.
- Exact state-address grounding recovered 38/48 cases when the original recovery language was sufficient.
- Extending the recovery calculus raised oracle recovery to 191/197 and enabled recovery on 142/143 failures attributed to insufficient language expressivity.