3.1k citations · 3.4k across the 8 of their papers we have counts for
10 papers
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…
The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations
Vipula Rawte, Swagata Chakraborty, Agnibh Pathak +5
The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has paralle…
AfroDigits: A Community-Driven Spoken Digit Dataset for African Languages
Chris Chinenye Emezue, Sanchit Gandhi, Lewis Tunstall +10
The advancement of speech technologies has been remarkable, yet its integration with African languages remains limited due to the scarcity of African speech corpora. To address thi…
Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements
Leandro von Werra, Lewis Tunstall, Abhishek Thakur +16
Evaluation is a key part of machine learning (ML), yet there is a lack of support and tooling to enable its informed and systematic practice. We introduce Evaluate and Evaluation o…
Datasets: A Community Library for Natural Language Processing
Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite +29
The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community…
HuggingFace's Transformers: State-of-the-art Natural Language Processing
Thomas Wolf, Lysandre Debut, Victor Sanh +19
Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building hig…
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond +1
As Transfer Learning from large-scale pre-trained models becomes more prevalent in Natural Language Processing (NLP), operating these large models in on-the-edge and/or under const…
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
Thomas Wolf, Victor Sanh, Julien Chaumond +1
We introduce a new approach to generative data-driven dialogue systems (e.g. chatbots) called TransferTransfo which is a combination of a Transfer learning based training scheme an…
Continuous Learning in a Hierarchical Multiscale Neural Network
Thomas Wolf, Julien Chaumond, Clement Delangue
We reformulate the problem of encoding a multi-scale representation of a sequence in a language model by casting it in a continuous learning framework. We propose a hierarchical mu…
Meta-Learning a Dynamical Language Model
Thomas Wolf, Julien Chaumond, Clement Delangue
We consider the task of word-level language modeling and study the possibility of combining hidden-states-based short-term representations with medium-term representations encoded…