arXiv:2609.36838v1 Announce Type: cross
Abstract: Visual agents solve problems by interleaving reasoning with image operations, and on-policy distillation (OPD) provides guidance from a strong teache...
By Shaohang Wei, Feifan Song, Guangyue Peng, Wenhao Yu, Wei Li, Wen Luo, Yang Xu, Yufan Shen, Luke Mao, Yang Du, Asher Qin, Houfeng Wang
VeriCUA is a platform-agnostic framework that treats verification of computer-using agents as dynamic evidence gathering and assessment. It constructs a task rubric from available context, then selects GUI or code checks to resolve unmet requirements and combines their findings under explicit evidence rules. Experiments demonstrate that VeriCUA achieves higher agreement with reference labels than baseline methods, especially on hard offline cases and in rejecting false completion claims online.
By Qiushi Sun, Da Yu, Alexander Knop, Amer Sinha, Lingpeng Kong, Ben Kao, Ravi Kumar, Pritish Kamath
The paper introduces Mind2Web-Injection, a benchmark of 9,954 instruction‑screenshot pairs designed to evaluate whether vision‑language models (VLMs) use visual evidence when judging conflicts between on‑screen text and user instructions. Across six VLMs, models with similar overall precision can differ dramatically in Evidence‑Aligned Detection (EAD), revealing that verdict‑only metrics miss critical grounding failures. The authors also propose two training‑free interventions—ReadGate and CmdCompare—to improve evidence grounding and instruction‑command consistency, and argue for separate reporting of verdict correctness, evidence localization, and counterfactual responsiveness.
By Suyoung Lee, Myungsub Choi
arXiv:2608. 10827v1 Announce Type: cross Abstract: Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading evidence.
By Shengzhi Wang, Jun Yang, Kai Wu, Xiaozhong Ji, Yiwen Ye, Ziyang Chen, Mingliang Xiong, Wen Fang, Mingqing Liu, Mengyuan Xu, Miaoxuan Shan, Caiyan Liu, Bin He, Qingwen Liu
arXiv:2607. 24770v1 Announce Type: new Abstract: Procedural tasks such as furniture assembly and home repair impose substantial cognitive demands because users must interpret instructions, track task progress, reason about spatial state, and recover from errors while performing physical actions.
By Azizul Zahid, Subrata Biswas, Bashima Islam, Sai Swaminathan
VeriCUA is a platform-agnostic framework that verifies computer-using agents by treating verification as dynamic evidence gathering and assessment. It constructs a task rubric from available context, then selects GUI or code checks to resolve unmet requirements, combining findings under explicit evidence rules. Experiments demonstrate higher agreement with reference labels than baselines, especially on hard offline cases and in rejecting false completion claims online.