299 citations · 370 across the 20 of their papers we have counts for
24 papers
Single Sequence Prediction over Reasoning Graphs for Multi-hop QA
Gowtham Ramesh, Makesh Sreedhar, Junjie Hu
Recent generative approaches for multi-hop question answering (QA) utilize the fusion-in-decoder method~\cite{izacard-grave-2021-leveraging} to generate a single sequence output wh…
Multimodal Prompt Retrieval for Generative Visual Question Answering
Timothy Ossowski, Junjie Hu
Recent years have witnessed impressive results of pre-trained vision-language models on knowledge-intensive tasks such as visual question answering (VQA). Despite the recent advanc…
Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection
Rheeya Uppaal, Junjie Hu, Yixuan Li
Out-of-distribution (OOD) detection is a critical task for reliable predictions over text. Fine-tuning with pre-trained language models has been a de facto procedure to derive OOD…
Benchmarking Machine Translation with Cultural Awareness
Binwei Yao, Ming Jiang, Tara Bobinac +2
Translating culture-related content is vital for effective cross-cultural communication. However, many culture-specific items (CSIs) often lack viable translations across languages…
Domain-adapted large language models for classifying nuclear medicine reports
Zachary Huemann, Changhee Lee, Junjie Hu +2
With the growing use of transformer-based language models in medicine, it is unclear how well these models generalize to nuclear medicine which has domain-specific vocabulary and u…
Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources
Xinyan Velocity Yu, Akari Asai, Trina Chatterjee +2
While the NLP community is generally aware of resource disparities among languages, we lack research that quantifies the extent and types of such disparity. Prior surveys estimatin…
MIA 2022 Shared Task: Evaluating Cross-lingual Open-Retrieval Question Answering for 16 Diverse Languages
Akari Asai, Shayne Longpre, Jungo Kasai +6
We present the results of the Workshop on Multilingual Information Access (MIA) 2022 Shared Task, evaluating cross-lingual open-retrieval question answering (QA) systems in 16 typo…
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Tuan Dinh, Jy-yong Sohn, Shashank Rajput +5
Word translation without parallel corpora has become feasible, rivaling the performance of supervised methods. Recent findings have shown that the accuracy and robustness of unsupe…
Local Byte Fusion for Neural Machine Translation
Makesh Narsimhan Sreedhar, Xiangpeng Wan, Yu Cheng +1
Subword tokenization schemes are the dominant technique used in current NLP models. However, such schemes can be rigid and tokenizers built on one corpus do not adapt well to other…
AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages
Machel Reid, Junjie Hu, Graham Neubig +1
Reproducible benchmarks are crucial in driving progress of machine translation research. However, existing machine translation benchmarks have been mostly limited to high-resource…
Phrase-level Active Learning for Neural Machine Translation
Junjie Hu, Graham Neubig
Neural machine translation (NMT) is sensitive to domain shift. In this paper, we address this problem in an active learning setting where we can spend a given budget on translating…
Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
Po-Yao Huang, Mandela Patrick, Junjie Hu +3
This paper studies zero-shot cross-lingual transfer of vision-language models. Specifically, we focus on multilingual text-to-video search and propose a Transformer-based model tha…
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation
Sebastian Ruder, Noah Constant, Jan Botha +8
Machine learning has brought striking advances in multilingual natural language processing capabilities over the past year. For example, the latest techniques have improved the sta…
Explicit Alignment Objectives for Multilingual Bidirectional Encoders
Junjie Hu, Melvin Johnson, Orhan Firat +2
Pre-trained cross-lingual encoders such as mBERT (Devlin et al., 2019) and XLMR (Conneau et al., 2020) have proven to be impressively effective at enabling transfer-learning of NLP…
On Learning Language-Invariant Representations for Universal Machine Translation
Han Zhao, Junjie Hu, Andrej Risteski
The goal of universal machine translation is to learn to translate between any pair of languages, given a corpus of paired translated documents for \emph{a small subset} of all pai…
TICO-19: the Translation Initiative for Covid-19
Antonios Anastasopoulos, Alessandro Cattelan, Zi-Yi Dou +15
The COVID-19 pandemic is the worst pandemic to strike the world in over a century. Crucial to stemming the tide of the SARS-CoV-2 virus is communicating to vulnerable populations t…
Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting
Po-Yao Huang, Junjie Hu, Xiaojun Chang +1
Unsupervised machine translation (MT) has recently achieved impressive results with monolingual corpora only. However, it is still challenging to associate source-target sentences…
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
Junjie Hu, Sebastian Ruder, Aditya Siddhant +3
Much recent progress in applications of machine learning models to NLP has been driven by benchmarks that evaluate models across a wide variety of tasks. However, these broad-cover…
Domain Differential Adaptation for Neural Machine Translation
Zi-Yi Dou, Xinyi Wang, Junjie Hu +1
Neural networks are known to be data hungry and domain sensitive, but it is nearly impossible to obtain large quantities of labeled data for every domain we are interested in. This…
REO-Relevance, Extraness, Omission: A Fine-grained Evaluation for Image Captioning
Ming Jiang, Junjie Hu, Qiuyuan Huang +3
Popular metrics used for evaluating image captioning systems, such as BLEU and CIDEr, provide a single score to gauge the system's overall effectiveness. This score is often not in…
What Makes A Good Story? Designing Composite Rewards for Visual Storytelling
Junjie Hu, Yu Cheng, Zhe Gan +3
Previous storytelling approaches mostly focused on optimizing traditional metrics such as BLEU, ROUGE and CIDEr. In this paper, we re-examine this problem from a different angle, b…
Handling Syntactic Divergence in Low-resource Machine Translation
Chunting Zhou, Xuezhe Ma, Junjie Hu +1
Despite impressive empirical successes of neural machine translation (NMT) on standard benchmarks, limited parallel data impedes the application of NMT models to many language pair…
Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature Embeddings
Zi-Yi Dou, Junjie Hu, Antonios Anastasopoulos +1
The recent success of neural machine translation models relies on the availability of high quality, in-domain data. Domain adaptation is required when domain-specific data is scarc…
Automatic Estimation of Simultaneous Interpreter Performance
Craig Stewart, Nikolai Vogler, Junjie Hu +2
Simultaneous interpretation, translation of the spoken word in real-time, is both highly challenging and physically demanding. Methods to predict interpreter confidence and the ade…