arxiv
PublishedOctober 15, 2026 at 4:00 AM
Interlock: From Local Correctness to Task Completion in Long-Horizon Agents
Publisher summary· verbatim
arXiv:2610.19686v1 Announce Type: new Abstract: Large language model agents increasingly undertake long-horizon tasks in complex environments characterized by fragmented evidence, partially completed states, and dependencies across resources and artifacts. Existing agents may satisfy individual requ
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivKolab: Benchmarking Human-Agent Collaboration in Long-Horizon Workflows11harxivOpen Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans11harxivWorldCast: Exploring Intelligent Visual Generation in World State Prediction11harxivInterpreting Language Model Parameters11hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗