b'Bing Xiang'

research

∙ 05/30/2023

Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge

The open-ended Visual Question Answering (VQA) task requires AI models t...

0 XingYu Fu, et al. ∙

research

∙ 05/27/2023

Benchmarking Diverse-Modal Entity Linking with Generative Models

Entities can be expressed in diverse formats, such as texts, images, or ...

0 Sijia Wang, et al. ∙

research

∙ 05/25/2023

UNITE: A Unified Benchmark for Text-to-SQL Evaluation

A practical text-to-SQL system should generalize well on a wide variety ...

0 Wuwei Lan, et al. ∙

research

∙ 03/09/2023

Greener yet Powerful: Taming Large Code Generation Models with Quantization

ML-powered code generation aims to assist developers to write code in a ...

0 Xiaokai Wei, et al. ∙

research

∙ 02/28/2023

Linear Spaces of Meanings: the Compositional Language of VLMs

We investigate compositional structures in vector data embeddings from p...

0 Matthew Trager, et al. ∙

research

∙ 02/13/2023

STREET: A Multi-Task Structured Reasoning and Explanation Benchmark

We introduce STREET, a unified multi-task and multi-domain natural langu...

0 Danilo Ribeiro, et al. ∙

research

∙ 01/21/2023

Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Neural text-to-SQL models have achieved remarkable performance in transl...

0 Shuaichen Chang, et al. ∙

research

∙ 12/20/2022

ReCode: Robustness Evaluation of Code Generation Models

Code generation models have achieved impressive performance. However, th...

0 Shiqi Wang, et al. ∙

research

∙ 12/20/2022

CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context

While pre-trained language models (LM) for code have achieved great succ...

0 Yangruibo Ding, et al. ∙

research

∙ 12/17/2022

Importance of Synthesizing High-quality Data for Text-to-SQL Parsing

Recently, there has been increasing interest in synthesizing data to imp...

0 Yiyun Zhao, et al. ∙

research

∙ 10/26/2022

Multi-lingual Evaluation of Code Generation Models

We present MBXP, an execution-based code completion benchmark in 10+ pro...

0 Ben Athiwaratkun, et al. ∙

research

∙ 10/03/2022

ContraGen: Effective Contrastive Learning For Causal Language Model

Despite exciting progress in large-scale language generation, the expres...

0 Nihal Jain, et al. ∙

research

∙ 09/30/2022

DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases

Question answering over knowledge bases (KBs) aims to answer natural lan...

7 Donghan Yu, et al. ∙

research

∙ 09/28/2022

Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding

Most recent research on Text-to-SQL semantic parsing relies on either pa...

24 Jun Wang, et al. ∙

research

∙ 06/10/2022

REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction

Relation extraction is an important but challenging task that aims to ex...

0 Sheng Zhang, et al. ∙

research

∙ 03/21/2022

DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization

Large-scale pre-trained sequence-to-sequence models like BART and T5 ach...

0 Zheng Li, et al. ∙

research

∙ 10/20/2021

Contrastive Document Representation Learning with Graph Attention Networks

Recent progress in pretrained Transformer-based language models has show...

0 Peng Xu, et al. ∙

research

∙ 10/12/2021

Attention-guided Generative Models for Extractive Question Answering

We propose a novel method for applying Transformer models to extractive ...

13 Peng Xu, et al. ∙

research

∙ 09/27/2021

Multiplicative Position-aware Transformer Models for Language Understanding

Transformer models, which leverage architectural improvements like self-...

6 Zhiheng Huang, et al. ∙

research

∙ 09/12/2021

Pairwise Supervised Contrastive Learning of Sentence Representations

Many recent successes in sentence representation learning have been achi...

0 Dejiao Zhang, et al. ∙

research

∙ 08/05/2021

Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answering

The current state-of-the-art generative models for open-domain question ...

0 Alexander Hanbo Li, et al. ∙

research

∙ 05/10/2021

Improving Factual Consistency of Abstractive Summarization via Question Answering

A commonly observed problem with the state-of-the art abstractive summar...

0 Feng Nan, et al. ∙

research

∙ 04/18/2021

Generative Context Pair Selection for Multi-hop Question Answering

Compositional reasoning tasks like multi-hop question answering, require...

5 Dheeru Dua, et al. ∙

research

∙ 03/24/2021

Supporting Clustering with Contrastive Learning

Unsupervised clustering aims at discovering the semantic categories of d...

0 Dejiao Zhang, et al. ∙

research

∙ 02/18/2021

Entity-level Factual Consistency of Abstractive Text Summarization

A key challenge for abstractive summarization is ensuring factual consis...

0 Feng Nan, et al. ∙

research

∙ 01/14/2021

Structured Prediction as Translation between Augmented Natural Languages

We propose a new framework, Translation between Augmented Natural Langua...

7 Giovanni Paolini, et al. ∙

research

∙ 12/18/2020

Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

Most recently, there has been significant interest in learning contextua...

10 Peng Shi, et al. ∙

research

∙ 11/26/2020

Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction

In open-domain question answering, questions are highly likely to be amb...

0 Yifan Gao, et al. ∙

research

∙ 10/12/2020

End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems

We propose an end-to-end approach for synthetic QA data generation. Our ...

0 Siamak Shakeri, et al. ∙

research

∙ 10/06/2020

Beyond [CLS] through Ranking by Generation

Generative models for Information Retrieval, where ranking of documents ...

0 Cicero Nogueira dos Santos, et al. ∙

research

∙ 09/28/2020

Improve Transformer Models with Better Relative Position Embeddings

Transformer architectures rely on explicit position encodings in order t...

0 Zhiheng Huang, et al. ∙

research

∙ 09/22/2020

Embedding-based Zero-shot Retrieval through Query Generation

Passage retrieval addresses the problem of locating relevant passages, u...

0 Davis Liang, et al. ∙

research

∙ 09/15/2020

Augmented Natural Language for Generative Sequence Labeling

We propose a generative framework for joint sequence labeling and senten...

0 Ben Athiwaratkun, et al. ∙

research

∙ 04/24/2020

Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering

Question Answering (QA) is in increasing demand as the amount of informa...

0 Alexander R. Fabbri, et al. ∙

research

∙ 03/16/2020

TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding

Bidirectional Encoder Representations from Transformers (BERT) has recen...

0 Zhiheng Huang, et al. ∙

research

∙ 11/25/2019

Who did They Respond to? Conversation Structure Modeling using Masked Hierarchical Transformer

Conversation structure is useful for both understanding the nature of co...

0 Henghui Zhu, et al. ∙

research

∙ 10/17/2019

Universal Text Representation from BERT: An Empirical Study

We present a systematic investigation of layer-wise BERT activations for...

0 Xiaofei Ma, et al. ∙

research

∙ 08/22/2019

Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering

BERT model has been successfully applied to open-domain QA tasks. Howeve...

11 Zhiguo Wang, et al. ∙

research

∙ 07/24/2019

Topic Modeling with Wasserstein Autoencoders

We propose a novel neural topic model in the Wasserstein autoencoders (W...

0 Feng Nan, et al. ∙

research

∙ 05/15/2019

Passage Ranking with Weak Supervision

In this paper, we propose a weak supervision framework for neural rankin...

0 Peng Xu, et al. ∙

research

∙ 05/15/2019

Passage Ranking with Weak Supervsion

In this paper, we propose a weak supervision framework for neural rankin...

0 Peng Xu, et al. ∙

research

∙ 04/08/2019

WeNet: Weighted Networks for Recurrent Network Architecture Search

In recent years, there has been increasing demand for automatic architec...

0 Zhiheng Huang, et al. ∙

research

∙ 03/20/2019

OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations

We present a novel model called OCGAN for the classical problem of one-c...

22 Pramuditha Perera, et al. ∙

research

∙ 09/07/2018

Coherence-Aware Neural Topic Modeling

Topic models are evaluated based on their ability to describe documents ...

0 Ran Ding, et al. ∙

research

∙ 05/13/2018

Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering

Coreference resolution aims to identify in a text all mentions that refe...

0 Rui Zhang, et al. ∙

research

∙ 10/07/2017

Group Sparse CNNs for Question Classification with Answer Sets

Question classification is an important task with wide applications. How...

0 Mingbo Ma, et al. ∙

research

∙ 09/28/2017

Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks

Sentence-level classification and sequential labeling are two fundamenta...

0 Mingbo Ma, et al. ∙

research

∙ 04/20/2017

Improved Neural Relation Detection for Knowledge Base Question Answering

Relation detection is a core component for many NLP applications includi...

0 Mo Yu, et al. ∙

research

∙ 03/09/2017

A Structured Self-attentive Sentence Embedding

This paper proposes a new model for extracting an interpretable sentence...

0 Zhouhan Lin, et al. ∙

research

∙ 01/15/2017

Neural Models for Sequence Chunking

Many natural language understanding (NLU) tasks, such as shallow parsing...

0 Feifei Zhai, et al. ∙

Bing Xiang

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