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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.
Article
Citation
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.
Article
Citation
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.
Article
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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.
Article
Citation
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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.
Article
Citation
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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.
Article
Citation
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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.
Article
Citation
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.
Article
Citation
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.
Article
Citation
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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