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WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
The ability of large language models (LLMs) to mimic human-like intelligence has led to a surge in LLM-based autonomous agents. Though …
Léo Boisvert
,
Megh Thakkar
,
Maxime Gasse
,
Massimo Caccia
,
Thibault Le Sellier De Chezelles
,
Quentin Cappart
,
Nicolas Chapados
,
Alexandre Lacoste
,
Alexandre Drouin
NeurIPS Datasets and Benchmarks Track (NeurIPS Datasets), 2024.
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Representing Positional Information in Generative World Models for Object Manipulation
The ability to predict outcomes of interactions between embodied agents and objects is paramount in the robotic setting. While …
Stefano Ferraro
,
Pietro Mazzaglia
,
Tim Verbelen
,
Sai Rajeswar Mudumba
Learning Effective Abstractions for Planning, 2024.
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Fine-Tuning Web Agents: It Works, But It's Trickier Than You Think
Recent advancements in large language models (LLMs) have sparked interest in developing autonomous web agents capable of performing …
Massimo Caccia
,
Megh Thakkar
,
Léo Boisvert
,
Thibault Le Sellier De Chezelles
,
Alexandre Piche
,
Nicolas Chapados
,
Alexandre Drouin
,
Maxime Gasse
,
Alexandre Lacoste
NOW AI Conference (NOWAI), 2024.
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An Ecosystem for Web Agents: WorkArena, BrowserGym, AgentLab and more
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those …
Alexandre Lacoste
,
Maxime Gasse
,
Thibault Le Sellier De Chezelles
,
Massimo Caccia
,
Léo Boisvert
,
Megh Thakkar
,
Alexandre Drouin
,
Nicolas Chapados
Montreal AI Symposium (MAIS), 2024.
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Multimodal foundation world models for generalist embodied agents
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Aaron Courville
,
Sai Rajeswar Mudumba
Workshop at the International Conference of Machine Learning (ICML), 2024.
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WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on …
Alexandre Drouin
,
Maxime Gasse
,
Massimo Caccia
,
Issam H. Laradji
,
Manuel Del Verme
,
Tom Marty
,
Léo Boisvert
,
Megh Thakkar
,
Quentin Cappart
,
David Vazquez
,
Nicolas Chapados
,
Alexandre Lacoste
International Conference on Machine Learning (ICML), 2024.
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Evaluating In-Context Learning of Libraries for Code Generation
Contemporary Large Language Models (LLMs) exhibit a high degree of code generation and comprehension capability. A particularly …
Arkil Patel
,
Siva Reddy
,
Dzmitry Bahdanau
,
Pradeep Dasigi
North American Chapter of the Association for Computational Linguistics (NAACL), 2024.
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Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
The accurate modeling of dynamics in interactive environments is critical for successful long-range prediction. Such a capability could …
Arnab Mondal
,
Siba Smarak Panigrahi
,
Siamak Ravanbakhsh
,
Sai Rajeswar Mudumba
International Conference of Learning Representations (ICLR), 2024.
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IntentGPT: Few-shot Intent Discovery with Large Language Models
In today’s digitally driven world, dialogue systems play a pivotal role in enhancing user interactions, from customer service to …
Juan A. Rodriguez
,
Nicholas Botzer
,
David Vazquez
,
Christopher Pal
,
Marco Pedersoli
,
Issam H. Laradji
Workshop at the International Conference of Learning Representation (ICLR), 2024.
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WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on …
Alexandre Drouin
,
Maxime Gasse
,
Massimo Caccia
,
Issam H. Laradji
,
Manuel Del Verme
,
Tom Marty
,
David Vazquez
,
Nicolas Chapados
,
Alexandre Lacoste
Workshop at the International Conference of Learning Representation (ICLR), 2024.
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