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06/20/2023
HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
We introduce HK-LegiCoST, a new three-way parallel corpus of Cantonese-E...
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06/12/2023
A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation
Large language models such as BERT and the GPT series started a paradigm...
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05/23/2023
Exploring Representational Disparities Between Multilingual and Bilingual Translation Models
Multilingual machine translation has proven immensely useful for low-res...
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05/05/2023
In-context Learning as Maintaining Coherency: A Study of On-the-fly Machine Translation Using Large Language Models
The phenomena of in-context learning has typically been thought of as "l...
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10/25/2022
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport
Bilingual lexicons form a critical component of various natural language...
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10/11/2022
IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces
The ability to extract high-quality translation dictionaries from monoli...
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01/20/2022
Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
The advent of transformer-based models such as BERT has led to the rise ...
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09/26/2021
An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces
Much recent work in bilingual lexicon induction (BLI) views word embeddi...
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09/09/2021
Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoring
This article describes an efficient end-to-end speech translation (E2E-S...
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07/01/2021
ESPnet-ST IWSLT 2021 Offline Speech Translation System
This paper describes the ESPnet-ST group's IWSLT 2021 submission in the ...
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05/10/2021
Self-Guided Curriculum Learning for Neural Machine Translation
In the field of machine learning, the well-trained model is assumed to b...
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01/26/2021
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yoloxóchitl Mixtec
"Transcription bottlenecks", created by a shortage of effective human tr...
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10/25/2020
Orthros: Non-autoregressive End-to-end Speech Translation with Dual-decoder
Fast inference speed is an important goal towards real-world deployment ...
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08/18/2020
Very Deep Transformers for Neural Machine Translation
We explore the application of very deep Transformer models for Neural Ma...
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05/08/2020
Modeling Document Interactions for Learning to Rank with Regularized Self-Attention
Learning to rank is an important task that has been successfully deploye...
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04/21/2020
ESPnet-ST: All-in-One Speech Translation Toolkit
We present ESPnet-ST, which is designed for the quick development of spe...
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04/12/2020
When Does Unsupervised Machine Translation Work?
Despite the reported success of unsupervised machine translation (MT), t...
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03/05/2020
Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation
We explore best practices for training small, memory efficient machine t...
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02/22/2020
Machine Translation System Selection from Bandit Feedback
Adapting machine translation systems in the real world is a difficult pr...
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02/19/2020
Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning
Universal feature extractors, such as BERT for natural language processi...
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12/06/2019
Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation
Sequence-level knowledge distillation (SLKD) is a model compression tech...
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10/01/2019
Multilingual End-to-End Speech Translation
In this paper, we propose a simple yet effective framework for multiling...
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09/05/2019
Broad-Coverage Semantic Parsing as Transduction
We unify different broad-coverage semantic parsing tasks under a transdu...
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05/24/2019
A Call for Prudent Choice of Subword Merge Operations
Most neural machine translation systems are built upon subword units ext...
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05/21/2019
AMR Parsing as Sequence-to-Graph Transduction
We propose an attention-based model that treats AMR parsing as sequence-...
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05/14/2019
Curriculum Learning for Domain Adaptation in Neural Machine Translation
We introduce a curriculum learning approach to adapt generic neural mach...
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04/16/2019
Query Expansion for Cross-Language Question Re-Ranking
Community question-answering (CQA) platforms have become very popular fo...
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04/11/2019
Membership Inference Attacks on Sequence-to-Sequence Models
Data privacy is an important issue for "machine learning as a service" p...
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11/02/2018
An Empirical Exploration of Curriculum Learning for Neural Machine Translation
Machine translation systems based on deep neural networks are expensive ...
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10/30/2018
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension
We present a large-scale dataset, ReCoRD, for machine reading comprehens...
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09/24/2018
Stochastic Answer Networks for SQuAD 2.0
This paper presents an extension of the Stochastic Answer Network (SAN),...
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09/14/2018
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation
To better understand the effectiveness of continued training, we analyze...
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09/06/2018
Character-Aware Decoder for Neural Machine Translation
Standard neural machine translation (NMT) systems operate primarily on w...
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09/05/2018
BPE and CharCNNs for Translation of Morphology: A Cross-Lingual Comparison and Analysis
Neural Machine Translation (NMT) in low-resource settings and of morphol...
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06/05/2018
How Do Source-side Monolingual Word Embeddings Impact Neural Machine Translation?
Using pre-trained word embeddings as input layer is a common practice in...
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05/21/2018
Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction
Cross-lingual information extraction (CLIE) is an important and challeng...
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04/21/2018
Cross-lingual Semantic Parsing
We introduce the task of cross-lingual semantic parsing: mapping content...
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04/21/2018
Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds
Fine-grained entity typing is the task of assigning fine-grained semanti...
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04/21/2018
Stochastic Answer Networks for Natural Language Inference
We propose a stochastic answer network (SAN) to explore multi-step infer...
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12/10/2017
Stochastic Answer Networks for Machine Reading Comprehension
We propose a simple yet robust stochastic answer network (SAN) that simu...
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11/09/2017
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks
Reading comprehension (RC) is a challenging task that requires synthesis...
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04/24/2017
Streaming Word Embeddings with the Space-Saving Algorithm
We develop a streaming (one-pass, bounded-memory) word embedding algorit...
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01/15/2017
DyNet: The Dynamic Neural Network Toolkit
We describe DyNet, a toolkit for implementing neural network models base...
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11/02/2016
Ordinal Common-sense Inference
Humans have the capacity to draw common-sense inferences from natural la...
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08/07/2016
Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network
Language processing mechanism by humans is generally more robust than co...
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04/22/2016
Dependency Parsing with LSTMs: An Empirical Evaluation
We propose a transition-based dependency parser using Recurrent Neural N...
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08/16/2015
Depth-Gated LSTM
In this short note, we present an extension of long short-term memory (L...
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12/18/2014