arXiv (All)
open access
When Harnesses Lose the Signal: Causal Evaluation of Recovery in LLM Agents
Large language model agents rely on external harnesses to pass information between the model and its environment and to recover from execution errors. Yet recovery is usually judged only by average task success. This hides an important tension. The same operation can rescue a failing trajectory or d
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective#987487
- Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents#1145149
- Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents#1136882
- SRD-GUARD: A Defense Framework of LLMs via Semantic Rewriting and Joint Multi-Model Scoring for Latent Intent Exposure#974654
- Smarter by the Moment: Environment-Driven Dynamic Policies for Continual LLM Improvement#1160782
Record · ID 1155307
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive