Context-Enriched Natural Language Descriptions of Vessel Trajectories
2026-03-16T08:52:17Z•de4d9f08628f0db07ac21a3defbfb486c229ca4b17bf8b8510b780984c03abb2
AISAgentFuelLLMMonte-Carlo-Tree-SearchODRL-normalizationReBalanceToolTreeagentic-AIagentsanomaly-detectionbenchmarksevaluationflowsheet-simulationlogits-redistributionmarine-enginesmaritimemodel-modulationnatural-language-generationoverthinkingpredictive-maintenanceprocess-modellingreasoningtimeseriestool-planningtrajectory-abstraction
What happened
This document is an RSS feed of new arXiv CS/AI submissions (16 Mar 2026) covering 11 papers. Key themes include LLM agents and planning (tool planning with Monte Carlo tree search, agentic web agents, multi-agent routing via ant-colony optimization), efficiency and reasoning control for large reasoning models (ReBalance), model modulation without retraining (AIM / logits redistribution), evaluation frameworks and benchmarks for data-analysis agents operating on time series (AgentFuel), context-enriched representations and NL generation for vessel AIS trajectories, early anomaly detection for海
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_ai
- Record identifier
- de4d9f08628f0db07ac21a3defbfb486c229ca4b17bf8b8510b780984c03abb2
- Enrichment time
- 2026-03-16T08:52:17Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.