We introduce MADLAD-400, a manually audited, general domain 3T token
mon...
Recent works have explored text-guided image editing using diffusion mod...
Multilingual machine translation (MMT), trained on a mixture of parallel...
Despite recent successes with neural models for sign language translatio...
Image generation using diffusion can be controlled in multiple ways. In ...
For end-to-end speech translation, regularizing the encoder with the
Con...
Research on prompting has shown excellent performance with little or eve...
Fusing deep learning models trained on separately located clients into a...
End-to-end (E2E) speech-to-text translation (ST) often depends on pretra...
We propose a new representation for encoding 3D shapes as neural fields....
In this work, we study the effect of varying the architecture and traini...
Natural language understanding and generation models follow one of the t...
Document-level neural machine translation (DocNMT) delivers coherent
tra...
We propose a novel and flexible roof modeling approach that can be used ...
Due to the great potential in facilitating software development, code
ge...
Recently, it has been argued that encoder-decoder models can be made mor...
Independence assumptions during sequence generation can speed up inferen...
Information in speech signals is not evenly distributed, making it an
ad...
We propose a novel 3d shape representation for 3d shape reconstruction f...
Following previous work on automatic paraphrasing, we assess the feasibi...
Massively multilingual models for neural machine translation (NMT) are
t...
Sequence-to-sequence models usually transfer all encoder outputs to the
...
In this paper we propose a new framework for point cloud instance
segmen...
Layer normalization (LayerNorm) has been successfully applied to various...
The general trend in NLP is towards increasing model capacity and perfor...
Recurrent networks have achieved great success on various sequential tas...
It has been shown that the performance of neural machine translation (NM...
In this paper, we propose an additionsubtraction twin-gated recurrent ne...
Although neural machine translation(NMT) yields promising translation
pe...
With parallelizable attention networks, the neural Transformer is very f...
Partially inspired by successful applications of variational recurrent n...
Neural machine translation (NMT) heavily relies on an attention network ...
The vanilla attention-based neural machine translation has achieved prom...
In this paper, we propose a bidimensional attention based recursive
auto...
Models of neural machine translation are often from a discriminative fam...
Implicit discourse relation recognition is a crucial component for autom...
Humans comprehend the meanings and relations of discourses heavily relyi...