b'Lizhen Qu'

research

∙ 05/27/2023

FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph Parsing

Textual scene graph parsing has become increasingly important in various...

0 Zhuang Li, et al. ∙

research

∙ 05/22/2023

The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning

Multilingual semantic parsing aims to leverage the knowledge from the hi...

0 Zhuang Li, et al. ∙

research

∙ 05/08/2023

Language Independent Neuro-Symbolic Semantic Parsing for Form Understanding

Recent works on form understanding mostly employ multimodal transformers...

0 Bhanu Prakash Voutharoja, et al. ∙

research

∙ 05/02/2023

Turning Flowchart into Dialog: Plan-based Data Augmentation for Low-Resource Flowchart-grounded Troubleshooting Dialogs

Flowchart-grounded troubleshooting dialogue (FTD) systems, which follow ...

0 Haolan Zhan, et al. ∙

research

∙ 04/24/2023

SocialDial: A Benchmark for Socially-Aware Dialogue Systems

Dialogue systems have been widely applied in many scenarios and are now ...

0 Haolan Zhan, et al. ∙

research

∙ 03/02/2023

Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery

In this paper, we conduct the first study on spurious correlations for o...

0 Tao Feng, et al. ∙

research

∙ 02/16/2023

Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation

Existing work in document-level neural machine translation commonly conc...

0 Minghao Wu, et al. ∙

research

∙ 12/20/2022

When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods

With increasing privacy concerns on data, recent studies have made signi...

1 Zhuo Zhang, et al. ∙

research

∙ 12/18/2022

Let's Negotiate! A Survey of Negotiation Dialogue Systems

Negotiation is one of the crucial abilities in human communication, and ...

0 Haolan Zhan, et al. ∙

research

∙ 11/27/2022

Learning Object-Language Alignments for Open-Vocabulary Object Detection

Existing object detection methods are bounded in a fixed-set vocabulary ...

0 Chuang Lin, et al. ∙

research

∙ 10/11/2022

ViLPAct: A Benchmark for Compositional Generalization on Multimodal Human Activities

We introduce ViLPAct, a novel vision-language benchmark for human activi...

8 Terry Yue Zhuo, et al. ∙

research

∙ 02/27/2022

Variational Autoencoder with Disentanglement Priors for Low-Resource Task-Specific Natural Language Generation

In this paper, we propose a variational autoencoder with disentanglement...

0 Zhuang Li, et al. ∙

research

∙ 11/10/2021

Multimodal Transformer with Variable-length Memory for Vision-and-Language Navigation

Vision-and-Language Navigation (VLN) is a task that an agent is required...

0 Chuang Lin, et al. ∙

research

∙ 10/13/2021

Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model

The ability to generate natural-language questions with controlled compl...

0 Sheng Bi, et al. ∙

research

∙ 09/11/2021

Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers

This paper investigates continual learning for semantic parsing. In this...

0 Zhuang Li, et al. ∙

research

∙ 08/29/2021

Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs

Machine-learning-as-a-service (MLaaS) has attracted millions of users to...

0 Qiongkai Xu, et al. ∙

research

∙ 05/14/2021

Neural-Symbolic Commonsense Reasoner with Relation Predictors

Commonsense reasoning aims to incorporate sets of commonsense facts, ret...

0 Farhad Moghimifar, et al. ∙

research

∙ 02/02/2021

On Robustness of Neural Semantic Parsers

Semantic parsing maps natural language (NL) utterances into logical form...

0 Shuo Huang, et al. ∙

research

∙ 01/26/2021

Few-Shot Semantic Parsing for New Predicates

In this work, we investigate the problems of semantic parsing in a few-s...

0 Zhuang Li, et al. ∙

research

∙ 11/02/2020

Context Dependent Semantic Parsing: A Survey

Semantic parsing is the task of translating natural language utterances ...

0 Zhuang Li, et al. ∙

research

∙ 11/02/2020

COSMO: Conditional SEQ2SEQ-based Mixture Model for Zero-Shot Commonsense Question Answering

Commonsense reasoning refers to the ability of evaluating a social situa...

0 Farhad Moghimifar, et al. ∙

research

∙ 09/14/2019

ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation

In this paper, we describe ALTER, an auxiliary text rewriting tool that ...

0 Qiongkai Xu, et al. ∙

research

∙ 08/13/2018

D-PAGE: Diverse Paraphrase Generation

In this paper, we investigate the diversity aspect of paraphrase generat...

0 Qiongkai Xu, et al. ∙

research

∙ 07/14/2017

f-GANs in an Information Geometric Nutshell

Nowozin et al showed last year how to extend the GAN principle to all f-...

0 Richard Nock, et al. ∙

research

∙ 12/20/2016

Automatic Generation of Grounded Visual Questions

In this paper, we propose the first model to be able to generate visuall...

0 Shijie Zhang, et al. ∙

research

∙ 10/31/2016

Named Entity Recognition for Novel Types by Transfer Learning

In named entity recognition, we often don't have a large in-domain train...

0 Lizhen Qu, et al. ∙

research

∙ 09/13/2016

Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

We present a theoretically grounded approach to train deep neural networ...

0 Giorgio Patrini, et al. ∙

research

∙ 06/27/2016

STransE: a novel embedding model of entities and relationships in knowledge bases

Knowledge bases of real-world facts about entities and their relationshi...

0 Dat Quoc Nguyen, et al. ∙

research

∙ 06/21/2016

Neighborhood Mixture Model for Knowledge Base Completion

Knowledge bases are useful resources for many natural language processin...

0 Dat Quoc Nguyen, et al. ∙

research

∙ 04/21/2015

Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representation on Sequence Labelling Tasks

Word embeddings -- distributed word representations that can be learned ...

0 Lizhen Qu, et al. ∙

research

∙ 08/04/2014

Estimating Maximally Probable Constrained Relations by Mathematical Programming

Estimating a constrained relation is a fundamental problem in machine le...

0 Lizhen Qu, et al. ∙

Lizhen Qu

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