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Natural Language Processing
ServiceNow Research
Natural Language Processing
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. …
Oscar Manas
,
Pau Rodriguez
,
Saba Ahmadi
,
Aida Nematzadeh
,
Yash Goyal
,
Aishwarya Agrawal
European Chapter of the Association for Computational Linguistics (EACL), 2023.
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Leveraging Human Preferences to Master Poetry
Large language models have been fine-tuned to learn poetry via supervised learning on a dataset containing relevant examples. However, …
Rafael Pardinas
,
Gabriel Huang
,
David Vazquez
,
Alexandre Piche
AAAI Workshops, 2023.
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OCR-VQGAN: Taming Text-within-Image Generation
Synthetic image generation has recently experienced significant improvements in domains such as natural image or art generation. …
Juan A. Rodriguez
,
David Vazquez
,
Marco Pedersoli
,
Issam H. Laradji
,
Pau Rodriguez
Winter Conference on Applications of Computer Vision (WACV), 2023.
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Azimuth: Systematic Error Analysis for Text Classification
We present Azimuth, an open-source and easy-to-use tool to perform error analysis for text classification. Compared to other stages of …
Gabrielle Gauthier Melançon
,
Orlando Marquez
,
Lindsay Brin
,
Chris Tyler
,
Frédéric Branchaud-Charron
,
Joseph Marinier
,
Karine Grande
,
Di Le
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.
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On the Compositional Generalization Gap of In-Context Learning
Pretrained large generative language models have shown great performance on many tasks, but exhibit low compositional generalization …
Dzmitry Bahdanau
,
Arian Hosseini
,
Aaron Courville
,
Alessandro Sordoni
,
Ankit Vani
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.
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UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases …
Tianbao Xie
,
Chen Wu
,
Peng Shi
,
Ruiqi Zhong
,
Torsten Scholak
,
Michihiro Yasunaga
,
Chien-Sheng Wu
,
Ming Zhong
,
Pengcheng Yin
,
Sida I. Wang
,
Victor Zhong
,
Bailin Wang
,
Chengzu Li
,
Connor Boyle
,
Ansong Ni
,
Ziyu Yao
,
Dragomir Radev
,
Caiming Xiong
,
Lingpeng Kong
,
Rui Zhang
,
Noah A. Smith
,
Luke Zettlemoyer
,
Tao Yu
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.
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Breadth-First Pipeline Parallelism
We introduce Breadth-First Pipeline Parallelism, a novel training schedule which optimizes the combination of pipeline and data …
Joel Lamy Poirier
Workshop at the Neural Information Processing Systems (NeurIPS), 2022.
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A Planning based Neural-Symbolic Approach for Embodied Instruction Following
The ALFRED environment features an embodied agent following instructions and accomplishing tasks in simulated home environments. …
Xiaotian Liu
,
Hector Palacios
,
Christian Muise
Montreal AI Symposium (MAIS), 2022.
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Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
Data augmentation is a widely employed technique to alleviate the problem of data scarcity. In this work, we propose a prompting-based …
Gaurav Sahu
,
Pau Rodriguez
,
Issam H. Laradji
,
Parmida Atighhehchian
,
David Vazquez
,
Dzmitry Bahdanau
Montreal AI Symposium (MAIS), 2022.
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Explainable, Sensible and Virtuous Workplace Chatbots
We outline three research directions towards the practical implementation of explainable, sensible and virtuous chatbots for the …
Gabriel Huang
,
Valérie Bécaert
,
David Vazquez
Montreal AI Symposium (MAIS), 2022.
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