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Generative AI
ServiceNow AI Research
Generative AI
SantaCoder: don't reach for the stars!
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This …
Harm de Vries
,
Raymond Li
,
Joel Lamy Poirier
,
Dzmitry Bahdanau
,
Denis Kocetkov
,
Sean Hughes
Workshop at the International Conference on Learning Representations (ICLR), 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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Workflow discovery in low data regimes
Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can …
Amine El Hattami
,
Issam H. Laradji
,
Stefania Raimondo
,
David Vazquez
,
Pau Rodriguez
,
Christopher Pal
Transactions on Machine Learning Research, 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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Haptics-based Curiosity for Sparse-reward Tasks
Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks …
Sai Rajeswar Mudumba
,
Cyril Ibrahim
,
Nitin Surya
,
Florian Golemo
,
David Vazquez
,
Aaron Courville
,
Pedro O. Pinheiro
Conference on Robot Learning (CoRL), 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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Attention-based Neural Cellular Automata
Recent extensions of Cellular Automata (CA) have incorporated key ideas from modern deep learning, dramatically extending their …
Mattie Tesfaldet
,
Derek Nowrouzezahrai
,
Christopher Pal
Conference on Neural Information Processing Systems (NeurIPS), 2022.
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Exploring the Design Space of Generative Diffusion Processes for Sparse Graphs
We extend score-based generative diffusion processes (GDPs) to sparse graphs and other inherently discrete data, with a focus on …
Pierre-André Noël
,
Pau Rodriguez
Workshop at the Neural Information Processing Systems (NeurIPS), 2022.
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Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be …
Vikram Voleti
,
Alexia Jolicoeur-Martineau
,
Christopher Pal
Conference on Neural Information Processing Systems (NeurIPS), 2022.
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Code
Does entity abstraction help generative Transformers reason?
We study the utility of incorporating entity type abstractions into pre-trained Transformers and test these methods on four NLP tasks …
Nicolas Gontier
,
Siva Reddy
,
Christopher Pal
Transactions on Machine Learning Research, 2022.
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