WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
On the map: LLM reasoning → Reasoning for agents, planning and code
Abstract (arXiv)
The ability of large language models (LLMs) to mimic human-like intelligence has led to a surge in LLM-based autonomous agents. Though recent LLMs seem capable of planning and reasoning given user instructions, their effectiveness in applying these capabilities for autonomous task solving remains underexplored. This is especially true in enterprise settings, where automated agents hold the promise of a high impact. To fill this gap, we propose WorkArena++, a novel benchmark consisting of 682 tasks corresponding to realistic workflows routinely performed by knowledge workers. WorkArena++ is designed to evaluate the planning, problem-solving, logical/arithmetic reasoning, retrieval, and contextual understanding abilities of web agents. Our empirical studies across state-of-the-art LLMs and vision-language models (VLMs), as well as human workers, reveal several challenges for such models to serve as useful assistants in the workplace. In addition to the benchmark, we provide a mechanism to effortlessly generate thousands of ground-truth observation/action traces, which can be used for fine-tuning existing models. Overall, we expect this work to serve as a useful resource to help the community progress toward capable autonomous agents. The benchmark can be found at https://github.com/ServiceNow/WorkArena.
Key facts. Cited by 90 papers in the map (data through 14 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 8 of its 33 references that are in the map. First posted on arXiv 7 Jul 2024.
Builds on
8 of 33 references.
References · 8
- 2023GPT-4 Technical Reportcited by 18,396
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,224
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
- 2024WebVoyager: Building an End-to-End Web Agent with Large Multimodal Modelscited by 438
- 2023Language Models can Solve Computer Taskscited by 372
- 2023Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4Vcited by 299
- 2024WebLINX: Real-World Website Navigation with Multi-Turn Dialoguecited by 180
Built on by
Citing papers per year: 2024: 3; 2025: 26; 2026: 61.
90 papers.
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