SEAR introduces a dual-process agentic framework for image restoration that combines pruning-aware MCTS planning with self-evolving episodic memory to address greedy search and episodic amnesia limitations.
In: Proceedings of the 36th annual acm symposium on user interface software and technology
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
An agent-based framework that uses artifact contracts to dynamically configure medical imaging pipelines while ensuring deterministic reproducibility and provenance.
EgoSelf uses graph-based memory of user interactions to derive personalized profiles and predict future behaviors for egocentric assistants.
Subagent architectures deliver stable high-throughput optimization under tight time limits while agent teams enable deeper refactoring at the cost of higher fragility.
citing papers explorer
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Self-Evolving Agentic Image Restoration via Deliberate Planning and Intuitive Execution
SEAR introduces a dual-process agentic framework for image restoration that combines pruning-aware MCTS planning with self-evolving episodic memory to address greedy search and episodic amnesia limitations.
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An Artifact-based Agent Framework for Adaptive and Reproducible Medical Image Processing
An agent-based framework that uses artifact contracts to dynamically configure medical imaging pipelines while ensuring deterministic reproducibility and provenance.
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EgoSelf: From Memory to Personalized Egocentric Assistant
EgoSelf uses graph-based memory of user interactions to derive personalized profiles and predict future behaviors for egocentric assistants.
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An Empirical Study of Multi-Agent Collaboration for Automated Research
Subagent architectures deliver stable high-throughput optimization under tight time limits while agent teams enable deeper refactoring at the cost of higher fragility.