arXiv:2506. 01952v2 Announce Type: replace-cross Abstract: Powered by large language models (LLMs), web browsing agents operate graphical user interfaces in a human-like manner, offering a transparent and general framework for automating web-based tasks.
By Atsuyuki Miyai, Zaiying Zhao, Kazuki Egashira, Atsuki Sato, Tatsumi Sunada, Shota Onohara, Hiromasa Yamanishi, Mashiro Toyooka, Kunato Nishina, Ryoma Maeda, Kiyoharu Aizawa, Toshihiko Yamasaki
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:2606. 05342v1 Announce Type: new Abstract: AI agents are increasingly asked to carry out work that spans minutes, hours, or longer.
By Matheus Kunzler Maldaner, Adam Fourney, Amanda Swearngin, Hussein Mozzanar, Gagan Bansal, Maya Murad, Rafah Hosn, Saleema Amershi
A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science .
By Shuai Guo
arXiv:2607. 06624v1 Announce Type: new Abstract: We present AgentLens, a production-assessed benchmark for interactive code agents.
By Andrey Podivilov, Vadim Lomshakov, Sergey Savin, Matvei Startsev, Roman Pozharskiy, Maksim Parshin, Sergey Nikolenko
arXiv:2607. 20482v1 Announce Type: new Abstract: Recent advances in large language models have enabled web agents to autonomously execute complex tasks.
By Seungbin Yang, Chaewoon Ki, Dohyun Lee, Jaegul Choo, ChaeHun Park
arXiv:2604. 04226v2 Announce Type: replace-cross Abstract: The Agentic Web is emerging as a paradigm in which autonomous software agents interact with online resources and with each other to accomplish user goals.
By Linyao Chen, Bo Huang, Qinlao Zhao, Shuai Shao, Zhi Han, Zicai Cui, Ziheng Zhang, Guangtao Zeng, Wenzheng Tang, Yikun Wang, Yuanjian Zhou, Zimian Peng, Yong Yu, Weiwen Liu, Hiroki Kobayashi, Weinan Zhang
arXiv:2510. 09801v3 Announce Type: replace Abstract: While benchmarks measure the accuracy of LLM-powered agents, they mostly assume full automation, failing to represent the collaborative nature of real-world use cases.
By Valerie Chen, Rohit Malhotra, Xingyao Wang, Juan Michelini, Xuhui Zhou, Aditya Bharat Soni, Hoang H. Tran, Calvin Smith, Ameet Talwalkar, Graham Neubig
arXiv:2511. 12997v2 Announce Type: replace Abstract: Multimodal LLM-powered agents have recently demonstrated impressive capabilities in web navigation, enabling agents to complete complex browsing tasks across diverse domains.
By Genglin Liu, Shijie Geng, Sha Li, Hejie Cui, Sarah Zhang, Xin Liu, Tianyi Liu
arXiv:2604. 06367v2 Announce Type: replace-cross Abstract: Web agents automate browser tasks, ranging from simple form completion to complex workflows like ordering groceries.
By Guruprasad Viswanathan Ramesh, Asmit Nayak, Basieem Siddique, Kassem Fawaz
arXiv:2606. 17698v1 Announce Type: new Abstract: As LLM-based shopping agents enter production, existing benchmarks fail to capture how a shopper's requirements arrive: stated implicitly in the query, recorded in a profile, or revealed only when the right question is asked.
By Zeyao Du, Tong Li, Haibo Zhang