arXiv AI

Navigation Alone Is Not Enough: Evaluating Explanatory Assistive UI Agents

arXiv:2608. 09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure behind visual layout.

arXiv AI
Aug 11

CAP: A Scalable Benchmark for Evaluating Cross-Site Browser Agents with Complex Actions and Perception

arXiv:2608. 08392v1 Announce Type: new Abstract: Large language models are increasingly deployed as autonomous agents that interact with the web through browsers.

By Zejun Xu, Taiyi Chen, Jin Li, Yongtong Gu, Qi Cheng, Aixuan Lv, Shuai Zhu, Pengfei Zhu, Kaichen Yang, Boyu Sun, Yixian Yang, Mulong Xie, Xin Liu, Dagang Li, Xiaoteng Ma, Hongru Wang
arXiv AI
Jul 22

Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents

arXiv:2506. 17913v2 Announce Type: replace Abstract: Graphical User Interface (GUI) agents have made significant progress in automating digital tasks through the utilization of computer vision and language models.

By Jinjie Wei, Jiyao Liu, Lihao Liu, Ming Hu, Junzhi Ning, Mingcheng Li, Weijie Yin, Junjun He, Xiao Liang, Chao Feng, Dingkang Yang
arXiv AI
Jul 29

ProcAgent: An Agentic Framework for Procedural Task Guidance on Edge with Human-in-the-Loop

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
arXiv AI
Jun 18

Signals of Provenance: Practices & Challenges of Navigating Indicators in AI-Generated Media for Sighted and Blind Individuals

arXiv:2505. 16057v2 Announce Type: replace-cross Abstract: AI-Generated (AIG) content has become increasingly widespread by recent advances in generative models and the easy-to-use tools that have significantly lowered the technical barriers for producing highly realistic audio, images, and videos through simple natural language prompts.

By Ayae Ide, Tory Park, Jaron Mink, Tanusree Sharma
arXiv Machine Learning
Jun 15

Running the Gauntlet: Re-evaluating the Capabilities of Agents Beyond Familiar Environments

arXiv:2606. 14397v1 Announce Type: new Abstract: As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabilities.

By Mykola Vysotskyi, Runqi Lin, Grzegorz Biziel, Michal Zakrzewski, Sebastian Montagna, Damian Rynczak, Shreyansh Padarha, Kumail Alhamoud, Zihao Fu, William Lugoloobi, Kai Rawal, Hanna Yershova, Xander Davies, Taras Rumezhak, Guohao Li, Fazl Barez, Baoyuan Wu, Arkadiusz Drohomirecki, Yarin Gal, Chris Russell, Christopher Summerfield, Adam Mahdi, Volodymyr Karpiv, Philip Torr, Adel Bibi