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long-horizon-agents

topic3 events
papersTODAY 04:00 UTC

arXiv Paper Proposes Adaptive Harness for Long-Horizon Clinical LLM Agents

A new arXiv preprint introduces Asclepius, a harness designed to keep LLM agents stable during long clinical tasks rather than short single-step prompts. The authors evaluate it in a Clinical Environment Simulator where an agent handles extended workflows under resource contention, arguing that current benchmarks miss this class of failures. The work targets reliability problems that appear only in hours-long deployments.

agents/healthcare/benchmarks/llm-agents
papersTODAY 04:00 UTC

Paper Frames Root-Cause Attribution as Search for Long-Horizon Agent Failures

A new arXiv preprint argues that identifying why long-horizon AI agents fail is best treated as a search problem over large execution logs. The approach aims to turn outcome-level failure signals into targeted fixes by locating the specific steps that caused a breakdown. The work targets reliability engineering for agents deployed on extended, multi-step tasks.

agents/safety/research/reliability
papersSEP 12 04:00 UTC

Paper Proposes Environment-Probing Curation for Enterprise Agent Memory

A new arXiv paper addresses how persistent memory is being adopted in production agent platforms so long-horizon agents can retain experience across sessions. The authors argue that curator agents limited to completed task traces can lock in mistakes and draw overly broad conclusions from incomplete evidence, and propose probing the environment as an alternative approach to memory curation.

agents/memory/enterprise/research