SkillShift-Bench: Benchmarking Skill Learning under Environment Evolution for Web Agents

arXiv cs.AIOctober 27, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.33528v1 Announce Type: new Abstract: Skill learning enables web agents to reuse prior experience for long-horizon interactive tasks. However, learned skills are typically evaluated in closed environments, overlooking the fact that real-world web deployment involves continuous shifts in invocation context, perceptual grounding, and execution feasibility. To this end, we introduce SkillShift-Bench, the first benchmark for evaluating skill learning with controlled open-environment shifts. SkillShift-Bench simulates Contextual Shift, Perceptual Shift, and Execution Shift across three self-hosted web systems, and evaluates agents with diagnostics covering task success, interaction cost

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