RESEARCHMonitorWATCHLIST
When Should Agents Remember? Falsification-Gated Self-Evolution for LLM Agents
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers introduced Falsification-Gated Self-Evolution to prevent LLM agents from writing unverified local lessons into long-term memory.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 11 November 2026
- Collected by OneBench
- 12 Nov 2026, 02:02 UK
Stored source excerpt
arXiv:2611.14326v1 Announce Type: cross Abstract: LLM agents increasingly operate in long-horizon, verifier-rich environments, but current self-improvement mechanisms often write episode-derived lessons directly into memory, making…
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