Behavioral Couplings: From Formation to Behavioral Emergence in Language Models
arXiv:2610.23847v1 Announce Type: cross Abstract: Fine-tuning large language models (LLMs) can induce behaviors beyond those explicitly targeted. For example, training…
Does On-Policy Distillation Need to Complete Every Rollout?
arXiv:2610.21337v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) effectively transfers capabilities from a teacher to a student through feedback on…
Structured Authority Injection: Persistent Human Control for LLM Agents via Typed MCP Overrides
arXiv:2610.22373v1 Announce Type: new Abstract: LLM-based agents are increasingly used as autonomous orchestrators in distributed and multi-agent systems, yet a…
Towards understanding and monitorability of reasoning LLMs
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,…
Reusability report: multi-sample omics network inference operates in distinct robustness regimes defined by prior knowledge and data availability
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…
Hindsight-Privileged RLVR: Single-Rollout Token Credit Without Group Sampling
arXiv:2610.20497v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models from checked task outcomes, but assigning…
The World Won’t Wait: Evaluating and Teaching Agents Under a Live Clock
arXiv:2610.20665v1 Announce Type: new Abstract: Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls…
FIRM: Fisher-Informed Retention Merging for Federated LLM Unlearning
arXiv:2610.21720v1 Announce Type: cross Abstract: Federated LLM unlearning addresses targeted knowledge removal when forget and retain data remain distributed across…