collaborators

5 papers

cs.CL2026

CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling

Yifan Zhang, Yutong Dai, Viraj Prabhu +3

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 succes…

cs.AI2026

How Far Are Vision-Language Models from Constructing the Real World? A Benchmark for Physical Generative Reasoning

Luyu Yang, Yutong Dai, An Yan +3

The physical world is not merely visual; it is governed by rigorous structural and procedural constraints. Yet, the evaluation of vision-language models (VLMs) remains heavily skew…

cs.CV2025

WALT: Web Agents that Learn Tools

Viraj Prabhu, Yutong Dai, Matthew Fernandez +8

Web agents promise to automate complex browser tasks, but current methods remain brittle -- relying on step-by-step UI interactions and heavy LLM reasoning that break under dynamic…

cs.AI2025

SCUBA: Salesforce Computer Use Benchmark

Yutong Dai, Krithika Ramakrishnan, Jing Gu +8

We introduce SCUBA, a benchmark designed to evaluate computer-use agents on customer relationship management (CRM) workflows within the Salesforce platform. SCUBA contains 300 task…

cs.CL2025

CoAct-1: Computer-using Multi-Agent System with Coding Actions

Linxin Song, Yutong Dai, Viraj Prabhu +9

Autonomous agents that operate computers via Graphical User Interfaces (GUIs) often struggle with efficiency and reliability on complex, long-horizon tasks. While augmenting these…