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CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling
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Proposes CLIFT, which certifies URL-conditioned verification questions with a conformal tracker to densify GRPO rewards for web agents and to drive judge-free trajectory selection (CTS) at test time.
Problem
Web-agent RL suffers from sparse binary success rewards and costly frontier-LLM judges that are unavailable at deployment; test-time selection also lacks a judge-free signal.
Approach
A bank of polarity-tagged, URL-scoped natural-language verification questions is certified via Mondrian adaptive conformal tracking against a training-time judge; certified signed trust weights add a non-negative verifier term to per-step rewards and drive a conservative pairwise majority-vote selector over greedy and retry rollouts.
Key results
- On WAI 9-app slice, Gemma-4 + CLIFT + CTS (K=3) reaches 74.6% overall vs 61.8% base Gemma-4 and 70.1% for Gemini 3 Flash + BU.
- On VWA, GPT-5.5 + CLIFT + CTS (K=4) reaches 53.7 weighted average, narrowly above WALT's 52.9.
- On OM2W with canonical judge, GPT-5.5 high goes from 49.7 to 61.0 with CTS at K=4 (+11.3pp); Gemma-4 goes from 40.0 to 45.0.
Surprising findings
- Vanilla GRPO raises steps on successful trajectories (15.4 to 18.5) yet gains only 2.9 points, while CLIFT gains 10.8 points with fewer steps.
- The transferred OM2W bank certified 100 of 132 questions, including 25 negative-lift failure-mode questions.
Limitations
- Relies on a frontier judge (Claude Opus 4.6) during training and bank construction; judge bias cannot be detected beyond observed data.
- Transfer does not establish a universal bank across all web domains.
- VWA result exceeds WALT by only 0.8 points, within noise-level margin.
Experimental setup
Datasets: WebArena Infinity (WAI) training tasks synthesized VisualWebArena (VWA) training tasks synthesized Online Mind2Web (OM2W) rollouts for bank recalibration
Benchmarks: WebArena Infinity VisualWebArena Online Mind2Web
Metrics: success rate weighted average success rate
Baselines: Vanilla GRPO SGV WALT Claude Opus 4.6 Gemini 3 Flash + BU Qwen 3.5+ Kimi K2.5 GPT-5.5 low/high base
Builds on: GRPO Mondrian adaptive conformal inference CEGAR WebJudge
Closest papers by meaning
- How to Train Your LLM Web Agent: A Statistical Diagnosis (NeurIPS 2025 · similarity 0.87)
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- WebGym: Scaling Training Environments for Long-Horizon Visual Web Agents with Realistic Tasks (CVPR 2026 · similarity 0.86)
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