Search Results for author: Jing Huang

Found 39 papers, 13 papers with code

Semantic Categorization of Social Knowledge for Commonsense Question Answering

1 code implementation11 Sep 2021 Gengyu Wang, Xiaochen Hou, Diyi Yang, Kathleen McKeown, Jing Huang

Large pre-trained language models (PLMs) have led to great success on various commonsense question answering (QA) tasks in an end-to-end fashion.

Question Answering

On the Opportunities and Risks of Foundation Models

1 code implementation16 Aug 2021 Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, aditi raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.

Transfer Learning

Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System

no code implementations9 Jun 2021 Zichuan Lin, Jing Huang, BoWen Zhou, Xiaodong He, Tengyu Ma

Recent work (Takanobu et al., 2020) proposed the system-wise evaluation on dialog systems and found that improvement on individual components (e. g., NLU, policy) in prior work may not necessarily bring benefit to pipeline systems in system-wise evaluation.

Data Augmentation Goal-Oriented Dialog

Conversational AI Systems for Social Good: Opportunities and Challenges

no code implementations13 May 2021 Peng Qi, Jing Huang, Youzheng Wu, Xiaodong He, BoWen Zhou

Conversational artificial intelligence (ConvAI) systems have attracted much academic and commercial attention recently, making significant progress on both fronts.

TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text

no code implementations CVPR 2021 Amanpreet Singh, Guan Pang, Mandy Toh, Jing Huang, Wojciech Galuba, Tal Hassner

A crucial component for the scene text based reasoning required for TextVQA and TextCaps datasets involve detecting and recognizing text present in the images using an optical character recognition (OCR) system.

Optical Character Recognition Scene Text +1

UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks

1 code implementation3 May 2021 Jing Huang, Jie Yang

In this paper, we propose UniGNN, a unified framework for interpreting the message passing process in graph and hypergraph neural networks, which can generalize general GNN models into hypergraphs.

Graph Representation Learning

Residual Enhanced Multi-Hypergraph Neural Network

1 code implementation2 May 2021 Jing Huang, Xiaolin Huang, Jie Yang

Hypergraphs are a generalized data structure of graphs to model higher-order correlations among entities, which have been successfully adopted into various research domains.

Representation Learning

A Multiplexed Network for End-to-End, Multilingual OCR

no code implementations CVPR 2021 Jing Huang, Guan Pang, Rama Kovvuri, Mandy Toh, Kevin J Liang, Praveen Krishnan, Xi Yin, Tal Hassner

Recent advances in OCR have shown that an end-to-end (E2E) training pipeline that includes both detection and recognition leads to the best results.

Optical Character Recognition

Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification

no code implementations NAACL 2021 Xiaochen Hou, Peng Qi, Guangtao Wang, Rex Ying, Jing Huang, Xiaodong He, BoWen Zhou

Recent work on aspect-level sentiment classification has demonstrated the efficacy of incorporating syntactic structures such as dependency trees with graph neural networks(GNN), but these approaches are usually vulnerable to parsing errors.

Ensemble Learning General Classification +1

Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling

1 code implementation21 Oct 2020 Wenxuan Zhou, Kevin Huang, Tengyu Ma, Jing Huang

In this paper, we propose two novel techniques, adaptive thresholding and localized context pooling, to solve the multi-label and multi-entity problems.

Document-level Multi-Label Classification +1

Multi-hop Attention Graph Neural Network

1 code implementation29 Sep 2020 Guangtao Wang, Rex Ying, Jing Huang, Jure Leskovec

Currently, at every layer, attention is computed between connected pairs of nodes and depends solely on the representation of the two nodes.

Graph Representation Learning Knowledge Graph Completion +1

Inductive Learning on Commonsense Knowledge Graph Completion

1 code implementation19 Sep 2020 Bin Wang, Guangtao Wang, Jing Huang, Jiaxuan You, Jure Leskovec, C. -C. Jay Kuo

Here, we propose to study the inductive learning setting for CKG completion where unseen entities may present at test time.

Entity Embeddings Knowledge Graph Completion +2

Entity and Evidence Guided Relation Extraction for DocRED

no code implementations27 Aug 2020 Kevin Huang, Guangtao Wang, Tengyu Ma, Jing Huang

Document-level relation extraction is a challenging task which requires reasoning over multiple sentences in order to predict relations in a document.

Document-level Language Modelling +1

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation

no code implementations CVPR 2021 Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu

Our core innovation is the learning of a region-phrase score function, based on which an image-sentence score function is further constructed.

Contrastive Learning Knowledge Distillation +3

Improving Neural Language Generation with Spectrum Control

no code implementations ICLR 2020 Lingxiao Wang, Jing Huang, Kevin Huang, Ziniu Hu, Guangtao Wang, Quanquan Gu

Recent Transformer-based models such as Transformer-XL and BERT have achieved huge success on various natural language processing tasks.

Language Modelling Machine Translation +2

Speaker Diarization with Lexical Information

no code implementations13 Apr 2020 Tae Jin Park, Kyu J. Han, Jing Huang, Xiaodong He, Bo-Wen Zhou, Panayiotis Georgiou, Shrikanth Narayanan

This work presents a novel approach for speaker diarization to leverage lexical information provided by automatic speech recognition.

automatic-speech-recognition Speaker Diarization +1

Graph Sequential Network for Reasoning over Sequences

no code implementations4 Apr 2020 Ming Tu, Jing Huang, Xiaodong He, Bo-Wen Zhou

We validate the proposed GSN on two NLP tasks: interpretable multi-hop reading comprehension on HotpotQA and graph based fact verification on FEVER.

Fact Verification Machine Reading Comprehension +1

Deep Visual Waterline Detection within Inland Marine Environment

no code implementations24 Nov 2019 Jing Huang, Hengfeng Miao, Lin Li, Yuanqiao Wen, Changshi Xiao

This paper attempts to find a solution to guarantee the effectiveness of waterline detection for inland maritime applications with general digital camera sensor.

Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding

no code implementations ACL 2020 Yun Tang, Jing Huang, Guangtao Wang, Xiaodong He, Bo-Wen Zhou

Translational distance-based knowledge graph embedding has shown progressive improvements on the link prediction task, from TransE to the latest state-of-the-art RotatE.

Knowledge Graph Embedding Link Prediction

Speaker-invariant Affective Representation Learning via Adversarial Training

no code implementations4 Nov 2019 Haoqi Li, Ming Tu, Jing Huang, Shrikanth Narayanan, Panayiotis Georgiou

In this paper, we propose a machine learning framework to obtain speech emotion representations by limiting the effect of speaker variability in the speech signals.

Emotion Classification Representation Learning +1

Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents

1 code implementation1 Nov 2019 Ming Tu, Kevin Huang, Guangtao Wang, Jing Huang, Xiaodong He, Bo-Wen Zhou

Interpretable multi-hop reading comprehension (RC) over multiple documents is a challenging problem because it demands reasoning over multiple information sources and explaining the answer prediction by providing supporting evidences.

Learning-To-Rank Multi-Hop Reading Comprehension +1

Improving Graph Attention Networks with Large Margin-based Constraints

no code implementations25 Oct 2019 Guangtao Wang, Rex Ying, Jing Huang, Jure Leskovec

Graph Attention Networks (GATs) are the state-of-the-art neural architecture for representation learning with graphs.

Graph Attention Representation Learning

Relation Module for Non-answerable Prediction on Question Answering

no code implementations23 Oct 2019 Kevin Huang, Yun Tang, Jing Huang, Xiaodong He, Bo-Wen Zhou

In this paper, we aim to improve a MRC model's ability to determine whether a question has an answer in a given context (e. g. the recently proposed SQuAD 2. 0 task).

Machine Reading Comprehension Question Answering

Zero-shot Text-to-SQL Learning with Auxiliary Task

1 code implementation29 Aug 2019 Shuaichen Chang, PengFei Liu, Yun Tang, Jing Huang, Xiaodong He, Bo-Wen Zhou

Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task.


Multiple instance learning with graph neural networks

no code implementations12 Jun 2019 Ming Tu, Jing Huang, Xiaodong He, Bo-Wen Zhou

In this paper, we propose a new end-to-end graph neural network (GNN) based algorithm for MIL: we treat each bag as a graph and use GNN to learn the bag embedding, in order to explore the useful structural information among instances in bags.

Multiple Instance Learning

Improving Rotated Text Detection with Rotation Region Proposal Networks

no code implementations16 Nov 2018 Jing Huang, Viswanath Sivakumar, Mher Mnatsakanyan, Guan Pang

In this work, we extend the scene-text extraction system at Facebook, Rosetta, to efficiently handle text in various orientations.

Misinformation Region Proposal +1

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

1 code implementation11 Nov 2018 Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, Bo-Wen Zhou

The recent graph convolutional network (GCN) provides another way of learning graph node embedding by successfully utilizing graph connectivity structure.

Knowledge Base Completion Knowledge Graph Embedding +2

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

1 code implementation17 May 2018 Ilke Demir, Krzysztof Koperski, David Lindenbaum, Guan Pang, Jing Huang, Saikat Basu, Forest Hughes, Devis Tuia, Ramesh Raskar

We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which includes three public competitions for segmentation, detection, and classification tasks on satellite images.

Learning Two-Branch Neural Networks for Image-Text Matching Tasks

1 code implementation11 Apr 2017 Liwei Wang, Yin Li, Jing Huang, Svetlana Lazebnik

Image-language matching tasks have recently attracted a lot of attention in the computer vision field.

Text Matching Visual Grounding

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