research
∙
09/08/2023
Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts
Sparse Mixture-of-Experts models (MoEs) have recently gained popularity ...
share
research
∙
04/10/2023
On Robustness in Multimodal Learning
Multimodal learning is defined as learning over multiple heterogeneous i...
research
∙
01/19/2023
Self Supervision Does Not Help Natural Language Supervision at Scale
Self supervision and natural language supervision have emerged as two ex...
research
∙
10/18/2022
Perceptual Grouping in Vision-Language Models
Recent advances in zero-shot image recognition suggest that vision-langu...
research
∙
06/22/2022
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
We present the Pathways Autoregressive Text-to-Image (Parti) model, whic...
research
∙
04/06/2022
Simple and Effective Synthesis of Indoor 3D Scenes
We study the problem of synthesizing immersive 3D indoor scenes from one...
research
∙
12/15/2021
LongT5: Efficient Text-To-Text Transformer for Long Sequences
Recent work has shown that either (1) increasing the input length or (2)...
research
∙
12/15/2021
Large Dual Encoders Are Generalizable Retrievers
It has been shown that dual encoders trained on one domain often fail to...
research
∙
09/10/2021
MURAL: Multimodal, Multitask Retrieval Across Languages
Both image-caption pairs and translation pairs provide the means to lear...
research
∙
09/10/2021
A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations
Language agnostic and semantic-language information isolation is an emer...
research
∙
08/19/2021
Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models
We provide the first exploration of text-to-text transformers (T5) sente...
research
∙
05/18/2021
Pathdreamer: A World Model for Indoor Navigation
People navigating in unfamiliar buildings take advantage of myriad visua...
research
∙
02/11/2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Pre-trained representations are becoming crucial for many NLP and percep...
research
∙
01/12/2021
Cross-Modal Contrastive Learning for Text-to-Image Generation
The output of text-to-image synthesis systems should be coherent, clear,...
research
∙
12/28/2020
Universal Sentence Representation Learning with Conditional Masked Language Model
This paper presents a novel training method, Conditional Masked Language...
research
∙
11/07/2020
Text-to-Image Generation Grounded by Fine-Grained User Attention
Localized Narratives is a dataset with detailed natural language descrip...
research
∙
10/23/2020
Neural Passage Retrieval with Improved Negative Contrast
In this paper we explore the effects of negative sampling in dual encode...
research
∙
09/29/2020
Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation
Neural models that independently project questions and answers into a sh...
research
∙
07/03/2020
Language-agnostic BERT Sentence Embedding
We adapt multilingual BERT to produce language-agnostic sentence embeddi...
research
∙
05/13/2020
End-to-end Semantics-based Summary Quality Assessment for Single-document Summarization
ROUGE is the de facto criterion for summarization research. However, its...
research
∙
05/05/2020
MultiReQA: A Cross-Domain Evaluation for Retrieval Question Answering Models
Retrieval question answering (ReQA) is the task of retrieving a sentence...
research
∙
04/30/2020
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO
Image captioning datasets have proven useful for multimodal representati...
research
∙
04/29/2020
Zero-shot Neural Retrieval via Domain-targeted Synthetic Query Generation
Deep neural scoring models have recently been shown to improve ranking q...
research
∙
04/11/2020
LAReQA: Language-agnostic answer retrieval from a multilingual pool
We present LAReQA, a challenging new benchmark for language-agnostic ans...
research
∙
04/09/2020
Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve
Named Entity Recognition systems achieve remarkable performance on domai...
research
∙
04/08/2020
Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models
Named entity recognition systems perform well on standard datasets compr...
research
∙
08/30/2019
PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification
Most existing work on adversarial data generation focuses on English. Fo...
research
∙
08/28/2019
Learning a Multitask Curriculum for Neural Machine Translation
Existing curriculum learning research in neural machine translation (NMT...
research
∙
07/10/2019
ReQA: An Evaluation for End-to-End Answer Retrieval Models
Popular QA benchmarks like SQuAD have driven progress on the task of ide...
research
∙
07/09/2019
Multilingual Universal Sentence Encoder for Semantic Retrieval
We introduce two pre-trained retrieval focused multilingual sentence enc...
research
∙
06/20/2019
Hierarchical Document Encoder for Parallel Corpus Mining
We explore using multilingual document embeddings for nearest neighbor m...
research
∙
05/19/2019
Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction
Modern NLP systems require high-quality annotated data. In specialized d...
research
∙
02/22/2019
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax
In this paper, we present an approach to learn multilingual sentence emb...
research
∙
10/30/2018
Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model
Neural language models have been shown to achieve an impressive level of...
research
∙
08/29/2018
Review Helpfulness Prediction with Embedding-Gated CNN
Product reviews, in the form of texts dominantly, significantly help con...
research
∙
07/31/2018
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
This paper presents an effective approach for parallel corpus mining usi...
research
∙
06/11/2018
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature
We present a corpus of 5,000 richly annotated abstracts of medical artic...
research
∙
04/30/2018
Syntactic Patterns Improve Information Extraction for Medical Search
Medical professionals search the published literature by specifying the ...
research
∙
04/20/2018
Learning Semantic Textual Similarity from Conversations
We present a novel approach to learn representations for sentence-level ...
research
∙
03/29/2018
Universal Sentence Encoder
We present models for encoding sentences into embedding vectors that spe...
research
∙
04/03/2017
Combining Lexical and Syntactic Features for Detecting Content-dense Texts in News
Content-dense news report important factual information about an event i...
research
∙
02/26/2017
