Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As trajectories grow, task requirements, environment facts, prior attempts, diagnoses, and open subgoals can be buried in the context window or pushed beyond it, failing to influence decisions when needed. We call this failure mode "behavioral state decay". We study memory as an active intervention mechanism rather than passive retrieval. A separate me
Record details
Published: 8 July 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Healthcare · Agents & autonomy · Environment
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents
arXiv · 5 July 2026
The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy
arXiv · 13 July 2026
Recent advances in AI-based mobile robots for human companionship: survey
Artificial Intelligence Review · 29 June 2026
SR-Agent: An Experience-Driven Agentic Framework for Post-Ranking Strategies Refinement in E-Commerce Recommendation
arXiv · 20 July 2026
How Do Tool-Augmented LLM Agents Perform on Real-World Energy Analytics Tasks?
arXiv · 24 June 2026
Clinical Pathways as Safety Specifications for Physical AI in Hospital Wards
arXiv cs.CY · 23 July 2026
How to cite this record
ethics.ai (8 July 2026), “Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,” evidence record 1538, https://ethics.ai/record/1538 (originally published by HuggingFace Daily Papers).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.