arXiv (All)
open access
CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling
Open-source web agents are now strong enough to execute realistic browser tasks, but training them with reinforcement learning still depends on weak supervision: binary task success is too sparse for credit assignment, while frontier-language-model judges are too expensive to call at every step and
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling#1194418
- CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents#228184
- WebPageBench: Event-Level Verification and Controlled UI-Variant Generation for Web Agents#1129630
- Discriminative World Models for Web Agents#632822
- AdaptArena: Evaluating Test-Time Personalization of Web Agents#1131330
Record · ID 1215910
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive