Search Results for author: Devendra Singh Sachan

Found 14 papers, 11 papers with code

Questions Are All You Need to Train a Dense Passage Retriever

no code implementations21 Jun 2022 Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer

We introduce ART, a new corpus-level autoencoding approach for training dense retrieval models that does not require any labeled training data.

Denoising Language Modelling

Stronger Transformers for Neural Multi-Hop Question Generation

no code implementations22 Oct 2020 Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan, William Hamilton

In this work, we introduce a series of strong transformer models for multi-hop question generation, including a graph-augmented transformer that leverages relations between entities in the text.

Question Generation

Do Syntax Trees Help Pre-trained Transformers Extract Information?

1 code implementation EACL 2021 Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William Hamilton

Our empirical analysis demonstrates that these syntax-infused transformers obtain state-of-the-art results on SRL and relation extraction tasks.

named-entity-recognition Named Entity Recognition +2

Parameter Sharing Methods for Multilingual Self-Attentional Translation Models

1 code implementation WS 2018 Devendra Singh Sachan, Graham Neubig

In multilingual neural machine translation, it has been shown that sharing a single translation model between multiple languages can achieve competitive performance, sometimes even leading to performance gains over bilingually trained models.

Machine Translation Translation

When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?

1 code implementation NAACL 2018 Ye Qi, Devendra Singh Sachan, Matthieu Felix, Sarguna Janani Padmanabhan, Graham Neubig

The performance of Neural Machine Translation (NMT) systems often suffers in low-resource scenarios where sufficiently large-scale parallel corpora cannot be obtained.

Machine Translation Translation +1

XNMT: The eXtensible Neural Machine Translation Toolkit

1 code implementation WS 2018 Graham Neubig, Matthias Sperber, Xinyi Wang, Matthieu Felix, Austin Matthews, Sarguna Padmanabhan, Ye Qi, Devendra Singh Sachan, Philip Arthur, Pierre Godard, John Hewitt, Rachid Riad, Liming Wang

In this paper we describe the design of XNMT and its experiment configuration system, and demonstrate its utility on the tasks of machine translation, speech recognition, and multi-tasked machine translation/parsing.

Machine Translation speech-recognition +2

Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition

2 code implementations21 Nov 2017 Devendra Singh Sachan, Pengtao Xie, Mrinmaya Sachan, Eric P. Xing

We also show that BiLM weight transfer leads to a faster model training and the pretrained model requires fewer training examples to achieve a particular F1 score.

Language Modelling named-entity-recognition +2

Class Vectors: Embedding representation of Document Classes

no code implementations2 Aug 2015 Devendra Singh Sachan, Shailesh Kumar

Distributed representations of words and paragraphs as semantic embeddings in high dimensional data are used across a number of Natural Language Understanding tasks such as retrieval, translation, and classification.

General Classification Natural Language Understanding +2

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