Grammatical error correction: A survey of the state of the art
Abstract Grammatical Error Correction (GEC) is the task of automatically detecting and
correcting errors in text. The task not only includes the correction of grammatical errors, such …
correcting errors in text. The task not only includes the correction of grammatical errors, such …
A survey on deep semi-supervised learning
Deep semi-supervised learning is a fast-growing field with a range of practical applications.
This paper provides a comprehensive survey on both fundamentals and recent advances in …
This paper provides a comprehensive survey on both fundamentals and recent advances in …
Speak, read and prompt: High-fidelity text-to-speech with minimal supervision
E Kharitonov, D Vincent, Z Borsos… - Transactions of the …, 2023 - direct.mit.edu
We introduce SPEAR-TTS, a multi-speaker text-to-speech (TTS) system that can be trained
with minimal supervision. By combining two types of discrete speech representations, we …
with minimal supervision. By combining two types of discrete speech representations, we …
Palm: Scaling language modeling with pathways
A Chowdhery, S Narang, J Devlin, M Bosma… - Journal of Machine …, 2023 - jmlr.org
Large language models have been shown to achieve remarkable performance across a
variety of natural language tasks using few-shot learning, which drastically reduces the …
variety of natural language tasks using few-shot learning, which drastically reduces the …
Hallucinations in large multilingual translation models
NM Guerreiro, DM Alves, J Waldendorf… - Transactions of the …, 2023 - direct.mit.edu
Hallucinated translations can severely undermine and raise safety issues when machine
translation systems are deployed in the wild. Previous research on the topic focused on …
translation systems are deployed in the wild. Previous research on the topic focused on …
Learning inverse folding from millions of predicted structures
We consider the problem of predicting a protein sequence from its backbone atom
coordinates. Machine learning approaches to this problem to date have been limited by the …
coordinates. Machine learning approaches to this problem to date have been limited by the …
Competition-level code generation with alphacode
Y Li, D Choi, J Chung, N Kushman, J Schrittwieser… - Science, 2022 - science.org
Programming is a powerful and ubiquitous problem-solving tool. Systems that can assist
programmers or even generate programs themselves could make programming more …
programmers or even generate programs themselves could make programming more …
Finetuned language models are zero-shot learners
This paper explores a simple method for improving the zero-shot learning abilities of
language models. We show that instruction tuning--finetuning language models on a …
language models. We show that instruction tuning--finetuning language models on a …
Multiscale vision transformers
H Fan, B **ong, K Mangalam, Y Li… - Proceedings of the …, 2021 - openaccess.thecvf.com
Abstract We present Multiscale Vision Transformers (MViT) for video and image recognition,
by connecting the seminal idea of multiscale feature hierarchies with transformer models …
by connecting the seminal idea of multiscale feature hierarchies with transformer models …
A survey of text watermarking in the era of large language models
Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …
Historically, their capabilities and application scenarios were limited. However, recent …