AAAI 2026technical0 citations

RealWebAssist: A Benchmark for Long-Horizon Web Assistance with Real-World Users

Suyu Ye, Haojun Shi, Darren Shih, Hyokun Yun, Tanya G. Roosta, Tianmin Shu

Abstract

To achieve successful assistance with long-horizon web-based tasks, AI agents must be able to sequentially follow real-world user instructions over a long period. Unlike existing web-based agent benchmarks, sequential instruction following in the real world poses significant challenges beyond performing a single, clearly defined task. For instance, real-world human instructions can be ambiguous, require different levels of AI assistance, and may evolve over time, reflecting changes in the user

BibTeX
@inproceedings{aaai2026_realwebassistabe,
  title = {RealWebAssist: A Benchmark for Long-Horizon Web Assistance with Real-World Users},
  author = {Suyu Ye and Haojun Shi and Darren Shih and Hyokun Yun and Tanya G. Roosta and Tianmin Shu},
  booktitle = {AAAI 2026},
  year = {2026}
}
RealWebAssist: A Benchmark for Long-Horizon Web Assistance with Real-World Users · AAAI 2026