[Submitted on 14 Oct 2026]
Title:ECHOES: Seeing Beyond the Current Image via Recursive History Compression and Privileged On-Policy Distillation
View a PDF of the paper titled ECHOES: Seeing Beyond the Current Image via Recursive History Compression and Privileged On-Policy Distillation, by Tengda Guo (1) and 11 other authors
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Abstract:Long-horizon GUI agents rely on visual history to maintain task states, but retaining historical screenshots increases visual-token usage and inference costs, while textual summaries can discard critical state information, undermining long-horizon reliability. We propose ECHOES, which leverages training-time privileged information to guide textual history compression and strengthen long-horizon reasoning. Specifically, ECHOES adopts a Compression-Think-Action (CTA) format to recursively update a textual history state and reason. The same model, given privileged multi-image inputs, serves as a teacher that provides dense token-level on-policy distillation on student-generated CTA rollouts. Our Perception-Memory Fidelity (PMF) Gap-guided OPD-RL framework dynamically balances privileged distillation and task-reward optimization, with periodic teacher updates supporting continued improvement. We further introduce ECHOESBMK, a fine-grained diagnostic benchmark derived from real GUI agent failure trajectories to jointly evaluate visual perception and cross-modal state retention. Experiments on four GUI benchmarks and ECHOESBMK demonstrate substantial gains in task performance and memory fidelity. Without retaining historical screenshots at deployment, ECHOES achieves competitive performance with a favorable performance-inference-cost trade-off and exhibits positive zero-shot transfer to unseen visual planning tasks.
Comments: 22 pages, 7 figures, 13 tables
Subjects:
Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2610.22408 [cs.AI]
(or arXiv:2610.22408v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2610.22408
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Tengda Guo [view email] [v1] Wed, 14 Oct 2026 14:39:41 UTC (3,286 KB)
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