Countermem: world-model verified counter-factual memory for language agents
Read the original at arxiv.org→arXiv:2609.31874v1 Announce Type: new Abstract: Existing agent memory frameworks mainly create memory through an agent's interaction with the factual world, e.g., remembering feedback from actions taken to improve...
Original headline: "COUNTERMEM: World-Model Verified Counter-Factual Memory for Language Agents"
Coverage timeline
- Sep 29, 04:00 UTC arXiv cs.AI lead source COUNTERMEM: World-Model Verified Counter-Factual Memory for Language Agents
- Oct 1, 04:00 UTC arXiv cs.CL EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making
- Oct 1, 04:00 UTC arXiv cs.CL Personalized State-Transition-Aware Memory for Clinical Agents
- Oct 2, 04:00 UTC arXiv cs.AI Heavy-Tailed Memory Traces in Long-Horizon Language Agents