pith:ADUZIQ2I
ReVision: Scaling Computer-Use Agents via Temporal Visual Redundancy Reduction
ReVision removes redundant visual patches from agent history screenshots to cut token usage by 46 percent while raising success rates by 3 percent.
arxiv:2605.11212 v3 · 2026-05-11 · cs.CL
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Claims
when processing trajectories with 5 history screenshots using Qwen2.5-VL-7B, ReVision reduces token usage by approximately 46% on average while improving success rate by 3% over the no drop baseline. This establishes a clear efficiency gain, enabling agents to process longer trajectories with fewer tokens.
The learned patch selector accurately identifies and removes only redundant patches without discarding task-critical visual information required for correct agent actions.
ReVision reduces visual token usage by 46% on average in agent trajectories via a learned patch selector and improves success rates by 3% on three benchmarks, showing that history saturation stems from inefficient representations rather than lack of utility.
Receipt and verification
| First computed | 2026-06-09T01:04:43.527598Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ADUZIQ2IT4Y53I7FZWGL7RDVEE \
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Canonical record JSON
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