ServiceNow AI Research

Large Language Models

LitLLM: A Toolkit for Scientific Literature Review
LitLLM: A Toolkit for Scientific Literature Review
Literature reviews are an essential component of scientific research. We explore the zero-shot abilities of recent large language …
Shubham Agarwal, Abhay Puri, Issam H. Laradji, Laurent Charlin, Christopher Pal
ArXiv,  2024.
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M-RewardBench: Evaluating Reward Models in Multilingual Settings
M-RewardBench: Evaluating Reward Models in Multilingual Settings
Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the …
Srishti Gureja, Lester James V. Miranda, Shayekh Bin Islam, Rishabh Maheshwary, Drishti Sharma, Gusti Winata, Nathan Lambert, Sebastian Ruder, Sara Hooker, Marzieh Fadaee
ArXiv,  2024.
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MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization
MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization
Low-resource extractive text summarization is a vital but heavily underexplored area of research. Prior literature either focuses on …
Issam H. Laradji, Gaurav Sahu
ArXiv,  2024.
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StarCoder 2 and The Stack v2: The Next Generation
StarCoder 2 and The Stack v2: The Next Generation
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code …
Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Terry Yue Zhuo, Nii Osae Osae Dade, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Edoardo Abati, Yekun Chai, Xiangru Tang, Christopher Akiki, Chenghao Mou, Binyuan Hui, Nicolas Patry, Canwen Xu, Julian McAuley, Han Hu, Torsten Scholak, Sébastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, Mostofa Patwary, Nima Tajbakhsh, Yacine Jernite, Carlos Muñoz Ferrandis, Lingming Zhang, Sean Hughes, Thomas Wolf , Arjun Guha, Leandro von Werra, Harm de Vries, Alex Gu, Armel Zebaze, Evgenii Zheltonozhskii, Jian Zhu, Manan Dey, Marc Marone, Mayank Mishra, Muhtasham Oblokulov, Olivier Dehaene, Qian Liu, Tri Dao, Wenhao Yu, Niklas Muennighoff
ArXiv,  2024.
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StarVector: Generating Scalable Vector Graphics Code from Images and Text
StarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) have become integral in modern image rendering and graphic design applications due to their infinite …
Juan A. Rodriguez, Shubham Agarwal, Abhay Puri, Issam H. Laradji, Sai Rajeswar Mudumba, Pau Rodriguez, David Vazquez, Christopher Pal, Marco Pedersoli
ArXiv,  2024.
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TapeAgents: a Holistic Framework for Agent Development and Optimization
TapeAgents: a Holistic Framework for Agent Development and Optimization
We present TapeAgents, an agent framework that leverages a structured, replayable log (tape) of the agent session to facilitate all …
Dzmitry Bahdanau, Nicolas Gontier, Gabriel Huang, Ehsan Kamalloo, Rafael Pardinas, Alexandre Piche, Torsten Scholak, Oleh Shliazhko, Jordan Prince Tremblay, Karam Ghanem, Soham Parikh, Mitul Tiwari, Quaizar Vohra
ArXiv,  2024.
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The BigCode Project Governance Card
The BigCode Project Governance Card
This document serves as an overview of the different mechanisms and areas of governance in the BigCode project. It aims to support …
Sean Hughes, Harm de Vries, Jennifer Robinson, Carlos Muñoz Ferrandis, Loubna Ben Allal, Leandro von Werra, Jennifer Ding, Sébastien Paquet, Yacine Jernite
ArXiv,  2024.
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Capture the Flag: Uncovering Data Insights with Large Language Models
Capture the Flag: Uncovering Data Insights with Large Language Models
The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. …
Issam H. Laradji, Perouz Taslakian, Sai Rajeswar Mudumba, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vazquez, Christopher Pal, Alexandre Drouin
Workshop at the Neural Information Processing Systems (NeurIPS),  2023.
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Lag-Llama: A Foundation Model for Probabilistic Time Series Forecasting
Lag-Llama: A Foundation Model for Probabilistic Time Series Forecasting
In this work, we present Lag-Llama, a general-purpose probabilistic time series forecasting model trained on a large collection of time …
Kashif Rasul, Arjun Ashok, Marin Bilos, Andrew Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Hena Ghonia, Nadhir Hassen, Anderson Schneider, Sahil Garg, Alexandre Drouin, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish
Workshop at the Neural Information Processing Systems (NeurIPS),  2023.
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The Unsolved Challenges of LLMs in Open-Ended Web Tasks: A Case Study
The Unsolved Challenges of LLMs in Open-Ended Web Tasks: A Case Study
In this work, we investigate the challenges associated with developing goal-driven AI agents capable of performing open-ended tasks in …
Rim Assouel, Tom Marty, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Sai Rajeswar Mudumba, Hector Palacios, Quentin Cappart, David Vazquez, Nicolas Chapados, Maxime Gasse, Alexandre Lacoste
Workshop at the Neural Information Processing Systems (NeurIPS),  2023.
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