Search Results for author: Shafiq Joty

Found 118 papers, 34 papers with code

Response Selection for Multi-Party Conversations with Dynamic Topic Tracking

no code implementations EMNLP 2020 Weishi Wang, Steven C.H. Hoi, Shafiq Joty

While participants in a multi-party multi-turn conversation simultaneously engage in multiple conversation topics, existing response selection methods are developed mainly focusing on a two-party single-conversation scenario.

Disentanglement Multi-Task Learning +1

Effective Fine-Tuning Methods for Cross-lingual Adaptation

no code implementations EMNLP 2021 Tao Yu, Shafiq Joty

In this work, we propose a novel fine-tuning method based on co-training that aims to learn more generalized semantic equivalences as a complementary to multilingual language modeling using the unlabeled data in the target language.

Contrastive Learning Language Modelling +1

Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model

1 code implementation31 May 2022 Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw

Numerous recent work on unsupervised machine translation (UMT) implies that competent unsupervised translations of low-resource and unrelated languages, such as Nepali or Sinhala, are only possible if the model is trained in a massive multilingual environment, where theses low-resource languages are mixed with high-resource counterparts.

Disentanglement Translation +1

Data Selection Curriculum for Neural Machine Translation

no code implementations25 Mar 2022 Tasnim Mohiuddin, Philipp Koehn, Vishrav Chaudhary, James Cross, Shruti Bhosale, Shafiq Joty

In this work, we introduce a two-stage curriculum training framework for NMT where we fine-tune a base NMT model on subsets of data, selected by both deterministic scoring using pre-trained methods and online scoring that considers prediction scores of the emerging NMT model.

Machine Translation Translation

ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

1 code implementation Findings (ACL) 2022 Ahmed Masry, Do Xuan Long, Jia Qing Tan, Shafiq Joty, Enamul Hoque

To address the unique challenges in our benchmark involving visual and logical reasoning over charts, we present two transformer-based models that combine visual features and the data table of the chart in a unified way to answer questions.

Question Answering

SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization

1 code implementation ACL 2022 Mathieu Ravaut, Shafiq Joty, Nancy F. Chen

Sequence-to-sequence neural networks have recently achieved great success in abstractive summarization, especially through fine-tuning large pre-trained language models on the downstream dataset.

Abstractive Text Summarization Document Summarization +1

Chart-to-Text: A Large-Scale Benchmark for Chart Summarization

2 code implementations ACL 2022 Shankar Kantharaj, Rixie Tiffany Ko Leong, Xiang Lin, Ahmed Masry, Megh Thakkar, Enamul Hoque, Shafiq Joty

We also introduce a number of state-of-the-art neural models as baselines that utilize image captioning and data-to-text generation techniques to tackle two problem variations: one assumes the underlying data table of the chart is available while the other needs to extract data from chart images.

Data-to-Text Generation Image Captioning

Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation

1 code implementation ACL 2022 Chengwei Qin, Shafiq Joty

Existing continual relation learning (CRL) methods rely on plenty of labeled training data for learning a new task, which can be hard to acquire in real scenario as getting large and representative labeled data is often expensive and time-consuming.

Data Augmentation

Knowledge Based Multilingual Language Model

no code implementations22 Nov 2021 Linlin Liu, Xin Li, Ruidan He, Lidong Bing, Shafiq Joty, Luo Si

Knowledge enriched language representation learning has shown promising performance across various knowledge-intensive NLP tasks.

Knowledge Graphs Language Modelling +5

A Unified Speaker Adaptation Approach for ASR

1 code implementation EMNLP 2021 Yingzhu Zhao, Chongjia Ni, Cheung-Chi Leung, Shafiq Joty, Eng Siong Chng, Bin Ma

For model adaptation, we use a novel gradual pruning method to adapt to target speakers without changing the model architecture, which to the best of our knowledge, has never been explored in ASR.

Automatic Speech Recognition speech-recognition

Cascaded Fast and Slow Models for Efficient Semantic Code Search

no code implementations15 Oct 2021 Akhilesh Deepak Gotmare, Junnan Li, Shafiq Joty, Steven C. H. Hoi

The goal of natural language semantic code search is to retrieve a semantically relevant code snippet from a fixed set of candidates using a natural language query.

Code Search Re-Ranking

Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling

no code implementations ACL 2022 Prathyusha Jwalapuram, Shafiq Joty, Xiang Lin

Given the claims of improved text generation quality across various pre-trained neural models, we consider the coherence evaluation of machine generated text to be one of the principal applications of coherence models that needs to be investigated.

Coherence Evaluation Contrastive Learning +1

LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5

1 code implementation ICLR 2022 Chengwei Qin, Shafiq Joty

Existing approaches to lifelong language learning rely on plenty of labeled data for learning a new task, which is hard to obtain in most real scenarios.

Few-Shot Learning

Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation

no code implementations ICLR 2022 Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn, Shafiq Joty

Modern unsupervised machine translation systems mostly train their models by generating synthetic parallel training data from large unlabeled monolingual corpora of different languages through various means, such as iterative back-translation.

Translation Unsupervised Machine Translation

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

1 code implementation EMNLP 2021 Yue Wang, Weishi Wang, Shafiq Joty, Steven C. H. Hoi

We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers.

Clone Detection Code Generation +5

MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER

no code implementations ACL 2021 Linlin Liu, Bosheng Ding, Lidong Bing, Shafiq Joty, Luo Si, Chunyan Miao

With the source-language data as well as the translated data, a generation-based multilingual data augmentation method is introduced to further increase diversity by generating synthetic labeled data in multiple languages.

Cross-Lingual NER Data Augmentation +4

Remember What You have drawn: Semantic Image Manipulation with Memory

no code implementations27 Jul 2021 Xiangxi Shi, Zhonghua Wu, Guosheng Lin, Jianfei Cai, Shafiq Joty

Therefore, in this paper, we propose a memory-based Image Manipulation Network (MIM-Net), where a set of memories learned from images is introduced to synthesize the texture information with the guidance of the textual description.

Computer Vision Image Manipulation +1

A Conditional Splitting Framework for Efficient Constituency Parsing

no code implementations ACL 2021 Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, XiaoLi Li

We introduce a generic seq2seq parsing framework that casts constituency parsing problems (syntactic and discourse parsing) into a series of conditional splitting decisions.

Constituency Parsing Discourse Segmentation

Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation

1 code implementation14 Jun 2021 Xiang Lin, Simeng Han, Shafiq Joty

Advanced large-scale neural language models have led to significant success in many language generation tasks.

Text Generation

AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT

no code implementations Findings (ACL) 2021 Tasnim Mohiuddin, M Saiful Bari, Shafiq Joty

We show that AUGVIC helps to attenuate the discrepancies between relevant and distant-domain monolingual data in traditional back-translation.

Data Augmentation Machine Translation +1

RST Parsing from Scratch

no code implementations NAACL 2021 Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, XiaoLi Li

We introduce a novel top-down end-to-end formulation of document-level discourse parsing in the Rhetorical Structure Theory (RST) framework.

Discourse Segmentation

Addressing the Vulnerability of NMT in Input Perturbations

1 code implementation NAACL 2021 Weiwen Xu, Ai Ti Aw, Yang Ding, Kui Wu, Shafiq Joty

Neural Machine Translation (NMT) has achieved significant breakthrough in performance but is known to suffer vulnerability to input perturbations.

Machine Translation Translation

Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings

no code implementations11 Mar 2021 Linlin Liu, Thien Hai Nguyen, Shafiq Joty, Lidong Bing, Luo Si

We operationalize our framework by first proposing a novel sense-aware cross entropy loss to model word senses explicitly.

Cross-Lingual NER Cross-Lingual Word Embeddings +4

Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning

no code implementations28 Jan 2021 Amrita Saha, Shafiq Joty, Steven C. H. Hoi

Neural Module Networks (NMNs) have been quite successful in incorporating explicit reasoning as learnable modules in various question answering tasks, including the most generic form of numerical reasoning over text in Machine Reading Comprehension (MRC).

Dependency Parsing Language Modelling +2

DiP Benchmark Tests: Evaluation Benchmarks for Discourse Phenomena in MT

no code implementations1 Jan 2021 Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty, Dominika Basaj

Despite increasing instances of machine translation (MT) systems including extrasentential context information, the evidence for translation quality improvement is sparse, especially for discourse phenomena.

Machine Translation Translation

Self-Supervised Relationship Probing

no code implementations NeurIPS 2020 Jiuxiang Gu, Jason Kuen, Shafiq Joty, Jianfei Cai, Vlad Morariu, Handong Zhao, Tong Sun

Structured representations of images that model visual relationships are beneficial for many vision and vision-language applications.

Contrastive Learning Language Modelling +1

Pronoun-Targeted Fine-tuning for NMT with Hybrid Losses

1 code implementation EMNLP 2020 Prathyusha Jwalapuram, Shafiq Joty, Youlin Shen

Our sentence-level model shows a 0. 5 BLEU improvement on both the WMT14 and the IWSLT13 De-En testsets, while our contextual model achieves the best results, improving from 31. 81 to 32 BLEU on WMT14 De-En testset, and from 32. 10 to 33. 13 on the IWSLT13 De-En testset, with corresponding improvements in pronoun translation.

Machine Translation Translation

Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

1 code implementation EMNLP 2020 Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Decision Making Discourse Segmentation +2

UNISON: Unpaired Cross-lingual Image Captioning

no code implementations3 Oct 2020 Jiahui Gao, Yi Zhou, Philip L. H. Yu, Shafiq Joty, Jiuxiang Gu

In this work, we present a novel unpaired cross-lingual method to generate image captions without relying on any caption corpus in the source or the target language.

Image Captioning Machine Translation +1

Finding It at Another Side: A Viewpoint-Adapted Matching Encoder for Change Captioning

no code implementations ECCV 2020 Xiangxi Shi, Xu Yang, Jiuxiang Gu, Shafiq Joty, Jianfei Cai

In this paper, we propose a novel visual encoder to explicitly distinguish viewpoint changes from semantic changes in the change captioning task.


GeDi: Generative Discriminator Guided Sequence Generation

3 code implementations Findings (EMNLP) 2021 Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, Nazneen Fatema Rajani

While large-scale language models (LMs) are able to imitate the distribution of natural language well enough to generate realistic text, it is difficult to control which regions of the distribution they generate.

Linguistic Acceptability Word Embeddings

Efficient Constituency Parsing by Pointing

no code implementations ACL 2020 Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, Xiao-Li Li

We propose a novel constituency parsing model that casts the parsing problem into a series of pointing tasks.

Constituency Parsing

Cross-model Back-translated Distillation for Unsupervised Machine Translation

1 code implementation3 Jun 2020 Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen, Wu Kui, Ai Ti Aw

Recent unsupervised machine translation (UMT) systems usually employ three main principles: initialization, language modeling and iterative back-translation, though they may apply them differently.

Denoising Language Modelling +2

Unsupervised Word Translation with Adversarial Autoencoder

no code implementations CL 2020 Tasnim Mohiuddin, Shafiq Joty

Crosslingual word embeddings learned from monolingual embeddings have a crucial role in many downstream tasks, ranging from machine translation to transfer learning.

Machine Translation Transfer Learning +3

EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

1 code implementation26 May 2020 Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi

The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.

Decision Making Reading Comprehension

It's Morphin' Time! Combating Linguistic Discrimination with Inflectional Perturbations

1 code implementation ACL 2020 Samson Tan, Shafiq Joty, Min-Yen Kan, Richard Socher

Training on only perfect Standard English corpora predisposes pre-trained neural networks to discriminate against minorities from non-standard linguistic backgrounds (e. g., African American Vernacular English, Colloquial Singapore English, etc.).

Rethinking Coherence Modeling: Synthetic vs. Downstream Tasks

no code implementations EACL 2021 Tasnim Mohiuddin, Prathyusha Jwalapuram, Xiang Lin, Shafiq Joty

Although coherence modeling has come a long way in developing novel models, their evaluation on downstream applications for which they are purportedly developed has largely been neglected.

Coherence Evaluation Language Modelling +4

Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding

1 code implementation EMNLP 2020 Samson Tan, Shafiq Joty, Lav R. Varshney, Min-Yen Kan

Inflectional variation is a common feature of World Englishes such as Colloquial Singapore English and African American Vernacular English.

Morphological Inflection Translation

Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation

no code implementations30 Apr 2020 Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty, Dominika Basaj

Despite increasing instances of machine translation (MT) systems including contextual information, the evidence for translation quality improvement is sparse, especially for discourse phenomena.

Machine Translation Translation

LNMap: Departures from Isomorphic Assumption in Bilingual Lexicon Induction Through Non-Linear Mapping in Latent Space

no code implementations EMNLP 2020 Tasnim Mohiuddin, M Saiful Bari, Shafiq Joty

Most of the successful and predominant methods for bilingual lexicon induction (BLI) are mapping-based, where a linear mapping function is learned with the assumption that the word embedding spaces of different languages exhibit similar geometric structures (i. e., approximately isomorphic).

Bilingual Lexicon Induction Cross-Lingual Word Embeddings +1

VD-BERT: A Unified Vision and Dialog Transformer with BERT

1 code implementation EMNLP 2020 Yue Wang, Shafiq Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi

By contrast, in this work, we propose VD-BERT, a simple yet effective framework of unified vision-dialog Transformer that leverages the pretrained BERT language models for Visual Dialog tasks.

Answer Generation Visual Dialog

Tree-structured Attention with Hierarchical Accumulation

no code implementations ICLR 2020 Xuan-Phi Nguyen, Shafiq Joty, Steven C. H. Hoi, Richard Socher

Incorporating hierarchical structures like constituency trees has been shown to be effective for various natural language processing (NLP) tasks.

Natural Language Processing Text Classification +1

Pairwise Neural Machine Translation Evaluation

no code implementations IJCNLP 2015 Francisco Guzman, Shafiq Joty, Lluis Marquez, Preslav Nakov

We present a novel framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a pair of hypotheses, given the reference translation.

Machine Translation Sentence Embeddings +1

DiscoTK: Using Discourse Structure for Machine Translation Evaluation

no code implementations WS 2014 Shafiq Joty, Francisco Guzman, Lluis Marquez, Preslav Nakov

We present novel automatic metrics for machine translation evaluation that use discourse structure and convolution kernels to compare the discourse tree of an automatic translation with that of the human reference.

Machine Translation Translation

Zero-Resource Cross-Lingual Named Entity Recognition

1 code implementation22 Nov 2019 M Saiful Bari, Shafiq Joty, Prathyusha Jwalapuram

Recently, neural methods have achieved state-of-the-art (SOTA) results in Named Entity Recognition (NER) tasks for many languages without the need for manually crafted features.

Cross-Lingual NER Low Resource Named Entity Recognition +2

Global Thread-Level Inference for Comment Classification in Community Question Answering

no code implementations EMNLP 2015 Shafiq Joty, Alberto Barrón-Cedeño, Giovanni Da San Martino, Simone Filice, Lluís Màrquez, Alessandro Moschitti, Preslav Nakov

Community question answering, a recent evolution of question answering in the Web context, allows a user to quickly consult the opinion of a number of people on a particular topic, thus taking advantage of the wisdom of the crowd.

Community Question Answering General Classification

Resurrecting Submodularity for Neural Text Generation

no code implementations8 Nov 2019 Simeng Han, Xiang Lin, Shafiq Joty

The resulting attention module offers an architecturally simple and empirically effective method to improve the coverage of neural text generation.

Abstractive Text Summarization Text Generation

Data Diversification: A Simple Strategy For Neural Machine Translation

2 code implementations NeurIPS 2020 Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw

Our method achieves state-of-the-art BLEU scores of 30. 7 and 43. 7 in the WMT'14 English-German and English-French translation tasks, respectively.

Knowledge Distillation Machine Translation +1

Enhancing Attention with Explicit Phrasal Alignments

no code implementations25 Sep 2019 Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen

The attention mechanism is an indispensable component of any state-of-the-art neural machine translation system.

Language Modelling Machine Translation +1

A Unified Neural Coherence Model

no code implementations IJCNLP 2019 Han Cheol Moon, Tasnim Mohiuddin, Shafiq Joty, Xu Chi

In this paper, we propose a unified coherence model that incorporates sentence grammar, inter-sentence coherence relations, and global coherence patterns into a common neural framework.

Machine Translation Translation

Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite

2 code implementations IJCNLP 2019 Prathyusha Jwalapuram, Shafiq Joty, Irina Temnikova, Preslav Nakov

The ongoing neural revolution in machine translation has made it easier to model larger contexts beyond the sentence-level, which can potentially help resolve some discourse-level ambiguities such as pronominal anaphora, thus enabling better translations.

Machine Translation Translation

Hierarchical Pointer Net Parsing

1 code implementation IJCNLP 2019 Linlin Liu, Xiang Lin, Shafiq Joty, Simeng Han, Lidong Bing

Transition-based top-down parsing with pointer networks has achieved state-of-the-art results in multiple parsing tasks, while having a linear time complexity.

Discourse Parsing Inductive Bias

Watch It Twice: Video Captioning with a Refocused Video Encoder

no code implementations21 Jul 2019 Xiangxi Shi, Jianfei Cai, Shafiq Joty, Jiuxiang Gu

With the rapid growth of video data and the increasing demands of various applications such as intelligent video search and assistance toward visually-impaired people, video captioning task has received a lot of attention recently in computer vision and natural language processing fields.

Computer Vision Natural Language Processing +1

Discourse Analysis and Its Applications

no code implementations ACL 2019 Shafiq Joty, Giuseppe Carenini, Raymond Ng, Gabriel Murray

Discourse processing is a suite of Natural Language Processing (NLP) tasks to uncover linguistic structures from texts at several levels, which can support many downstream applications.

Machine Translation Natural Language Processing +4

Sentence-Level Evidence Embedding for Claim Verification with Hierarchical Attention Networks

no code implementations ACL 2019 Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications.

A Unified Linear-Time Framework for Sentence-Level Discourse Parsing

2 code implementations ACL 2019 Xiang Lin, Shafiq Joty, Prathyusha Jwalapuram, M Saiful Bari

We propose an efficient neural framework for sentence-level discourse analysis in accordance with Rhetorical Structure Theory (RST).

Discourse Parsing

Revisiting Adversarial Autoencoder for Unsupervised Word Translation with Cycle Consistency and Improved Training

1 code implementation NAACL 2019 Tasnim Mohiuddin, Shafiq Joty

Adversarial training has shown impressive success in learning bilingual dictionary without any parallel data by mapping monolingual embeddings to a shared space.

Translation Word Translation

Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach

no code implementations CL 2018 Shafiq Joty, Tasnim Mohiuddin

Participants in an asynchronous conversation (e. g., forum, e-mail) interact with each other at different times, performing certain communicative acts, called speech acts (e. g., question, request).

Word Embeddings

Adversarial Unsupervised Representation Learning for Activity Time-Series

no code implementations14 Nov 2018 Karan Aggarwal, Shafiq Joty, Luis Fernandez-Luque, Jaideep Srivastava

Sufficient physical activity and restful sleep play a major role in the prevention and cure of many chronic conditions.

Representation Learning Time Series

Reuse and Adaptation for Entity Resolution through Transfer Learning

no code implementations28 Sep 2018 Saravanan Thirumuruganathan, Shameem A Puthiya Parambath, Mourad Ouzzani, Nan Tang, Shafiq Joty

Entity resolution (ER) is one of the fundamental problems in data integration, where machine learning (ML) based classifiers often provide the state-of-the-art results.

Entity Resolution Feature Engineering +1

Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings

no code implementations EMNLP 2018 Shafiq Joty, Lluis Marquez, Preslav Nakov

We address jointly two important tasks for Question Answering in community forums: given a new question, (i) find related existing questions, and (ii) find relevant answers to this new question.

Community Question Answering

Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction

no code implementations8 Jul 2018 Xiangxi Shi, Jianfei Cai, Jiuxiang Gu, Shafiq Joty

In this paper, we propose a boundary-aware hierarchical language decoder for video captioning, which consists of a high-level GRU based language decoder, working as a global (caption-level) language model, and a low-level GRU based language decoder, working as a local (phrase-level) language model.

Language Modelling Text Generation +2

Domain Adaptation with Adversarial Training and Graph Embeddings

1 code implementation ACL 2018 Firoj Alam, Shafiq Joty, Muhammad Imran

In such scenarios, a DNN model can leverage labeled and unlabeled data from a related domain, but it has to deal with the shift in data distributions between the source and the target domains.

Domain Adaptation

Coherence Modeling of Asynchronous Conversations: A Neural Entity Grid Approach

1 code implementation ACL 2018 Tasnim Mohiuddin, Shafiq Joty, Dat Tien Nguyen

We propose a novel coherence model for written asynchronous conversations (e. g., forums, emails), and show its applications in coherence assessment and thread reconstruction tasks.

Graph Based Semi-supervised Learning with Convolution Neural Networks to Classify Crisis Related Tweets

no code implementations2 May 2018 Firoj Alam, Shafiq Joty, Muhammad Imran

During time-critical situations such as natural disasters, rapid classification of data posted on social networks by affected people is useful for humanitarian organizations to gain situational awareness and to plan response efforts.

General Classification Humanitarian

Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of Nodes

1 code implementation16 Apr 2018 Tanay Kumar Saha, Thomas Williams, Mohammad Al Hasan, Shafiq Joty, Nicholas K. Varberg

However, existing models for learning latent representation are inadequate for obtaining the representation vectors of the vertices for different time-stamps of a dynamic network in a meaningful way.

Link Prediction Representation Learning

VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions

no code implementations ECCV 2018 Qing Li, Qingyi Tao, Shafiq Joty, Jianfei Cai, Jiebo Luo

Most existing works in visual question answering (VQA) are dedicated to improving the accuracy of predicted answers, while disregarding the explanations.

Multi-Task Learning Question Answering +1

Unpaired Image Captioning by Language Pivoting

no code implementations ECCV 2018 Jiuxiang Gu, Shafiq Joty, Jianfei Cai, Gang Wang

Image captioning is a multimodal task involving computer vision and natural language processing, where the goal is to learn a mapping from the image to its natural language description.

Computer Vision Image Captioning +1

Hyperedge2vec: Distributed Representations for Hyperedges

no code implementations ICLR 2018 Ankit Sharma, Shafiq Joty, Himanshu Kharkwal, Jaideep Srivastava

We present a number of interesting baselines, some of which adapt existing node-level embedding models to the hyperedge-level, as well as sequence based language techniques which are adapted for set structured hypergraph topology.

Probabilistic Deep Learning

Discourse Structure in Machine Translation Evaluation

no code implementations CL 2017 Shafiq Joty, Francisco Guzmán, Lluís Màrquez, Preslav Nakov

In this article, we explore the potential of using sentence-level discourse structure for machine translation evaluation.

Machine Translation Translation

Cross-Language Question Re-Ranking

no code implementations4 Oct 2017 Giovanni Da San Martino, Salvatore Romeo, Alberto Barron-Cedeno, Shafiq Joty, Lluis Marquez, Alessandro Moschitti, Preslav Nakov

We compare a kernel-based system with a feed-forward neural network in a scenario where a large parallel corpus is available for training a machine translation system, bilingual dictionaries, and cross-language word embeddings.

Machine Translation Re-Ranking +1

DeepER -- Deep Entity Resolution

3 code implementations2 Oct 2017 Muhammad Ebraheem, Saravanan Thirumuruganathan, Shafiq Joty, Mourad Ouzzani, Nan Tang

word embeddings), we present a novel ER system, called DeepER, that achieves good accuracy, high efficiency, as well as ease-of-use (i. e., much less human efforts).


Cross-language Learning with Adversarial Neural Networks

no code implementations CONLL 2017 Shafiq Joty, Preslav Nakov, Llu{\'\i}s M{\`a}rquez, Israa Jaradat

We address the problem of cross-language adaptation for question-question similarity reranking in community question answering, with the objective to port a system trained on one input language to another input language given labeled training data for the first language and only unlabeled data for the second language.

Community Question Answering Domain Adaptation +3

A Neural Local Coherence Model

1 code implementation ACL 2017 Dat Tien Nguyen, Shafiq Joty

We propose a local coherence model based on a convolutional neural network that operates over the entity grid representation of a text.

Text Generation

Cross-language Learning with Adversarial Neural Networks: Application to Community Question Answering

no code implementations21 Jun 2017 Shafiq Joty, Preslav Nakov, Lluís Màrquez, Israa Jaradat

We address the problem of cross-language adaptation for question-question similarity reranking in community question answering, with the objective to port a system trained on one input language to another input language given labeled training data for the first language and only unlabeled data for the second language.

Community Question Answering Question Similarity

Dis-S2V: Discourse Informed Sen2Vec

1 code implementation25 Oct 2016 Tanay Kumar Saha, Shafiq Joty, Naeemul Hassan, Mohammad Al Hasan

Our first approach retrofits (already trained) Sen2Vec vectors with respect to the network in two different ways: (1) using the adjacency relations of a node, and (2) using a stochastic sampling method which is more flexible in sampling neighbors of a node.

Applications of Online Deep Learning for Crisis Response Using Social Media Information

no code implementations4 Oct 2016 Dat Tien Nguyen, Shafiq Joty, Muhammad Imran, Hassan Sajjad, Prasenjit Mitra

During natural or man-made disasters, humanitarian response organizations look for useful information to support their decision-making processes.

Decision Making Disaster Response +3

Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networks

no code implementations12 Aug 2016 Dat Tien Nguyen, Kamela Ali Al Mannai, Shafiq Joty, Hassan Sajjad, Muhammad Imran, Prasenjit Mitra

The current state-of-the-art classification methods require a significant amount of labeled data specific to a particular event for training plus a lot of feature engineering to achieve best results.

Classification Feature Engineering +1

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