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AgentMerge: Enhancing Generalization in Fine-Tuned LLM Agents
Recent advancements in large language models (LLMs) have spurred interest in developing autonomous agents capable of performing complex …
Megh Thakkar
,
Léo Boisvert
,
Thibault Le Sellier De Chezelles
,
Alexandre Piche
,
Maxime Gasse
,
Alexandre Lacoste
,
Massimo Caccia
Workshop at the Neural Information Processing Systems (NeurIPS), 2024.
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BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks
Vision and language models that can accurately understand both images and text are crucial for deeper document understanding. These …
Juan A. Rodriguez
,
Xiangru Jian
,
Siba Smarak Panigrahi
,
Tianyu Zhang
,
Aarash Feizi
,
Abhay Puri
,
Akshay Kalkunte
,
Francois Savard
,
Amirhossein Abaskohi
,
Ahmed Masry
,
Shravan Nayak
,
Mahsa Massoud
,
Rabiul Awal
,
Pierre-André Noël
,
Mats L. Richter
,
Saverio Vadacchino
,
Shubham Agarwal
,
Sanket Biswas
,
Ying Zhang
,
Sathwik Tejaswi Madhusudhan
,
João Monteiro
,
Krishnamurthy (Dj) Dvijotham
,
Torsten Scholak
,
Nicolas Chapados
,
Sean Hughes
,
Tamer Özsu
,
Aishwarya Agrawal
,
Marco Pedersoli
,
Christopher Pal
,
Perouz Taslakian
,
David Vazquez
,
Issam H. Laradji
,
Spandana Gella
,
Sai Rajeswar Mudumba
Workshop at the Neural Information Processing Systems (NeurIPS), 2024.
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Code
Video
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
Workshop at the Neural Information Processing Systems (NeurIPS), 2024.
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Multimodal foundation world models for generalist embodied agents
Learning generalist agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement learning …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Aaron Courville
,
Sai Rajeswar Mudumba
Neural Information Processing Systems (NeurIPS), 2024.
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Code
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
Large Language Models (LLMs) are trained on vast amounts of data, most of which is automatically scraped from the internet. This data …
João Monteiro
,
Pierre-André Noël
,
Étienne Marcotte
,
Sai Rajeswar Mudumba
,
Valentina Zantedeschi
,
David Vazquez
,
Nicolas Chapados
,
Christopher Pal
,
Perouz Taslakian
NeurIPS Datasets and Benchmarks Track (NeurIPS Datasets), 2024.
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Code
Video
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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Code
Video
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.
Cite
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.
PDF
Cite
Code
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