by ODEFTO AI Labs
arXiv:2610.21682v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) can become off-policy due to training-inference mismatch, mini-batch updates, and asynchronous training.…
arXiv:2610.22373v1 Announce Type: new Abstract: LLM-based agents are increasingly used as autonomous orchestrators in distributed and multi-agent systems, yet a…
Nature Machine Intelligence, Published online: 19 October 2026; doi:10.1038/s42256-026-01333-6 Frontier LLMs are trained to solve problems in a step-by-step way,…
Nature Machine Intelligence, Published online: 19 October 2026; doi:10.1038/s42256-026-01311-y This work studies the reusability of CORNETO, a previously developed framework…
arXiv:2610.20243v2 Announce Type: replace-cross Abstract: Anomaly detection is a fundamental task for time-series analytics, with important implications for the downstream…
arXiv:2610.21720v1 Announce Type: cross Abstract: Federated LLM unlearning addresses targeted knowledge removal when forget and retain data remain distributed across…
arXiv:2610.21731v1 Announce Type: cross Abstract: Web search allows LLMs to access up-to-date information, but it remains unclear why they sometimes…
arXiv:2610.20497v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models from checked task outcomes, but assigning…