b'Chongyang Tao'

research

∙ 05/26/2023

UMSE: Unified Multi-scenario Summarization Evaluation

Summarization quality evaluation is a non-trivial task in text summariza...

0 Shen Gao, et al. ∙

research

∙ 05/22/2023

MADNet: Maximizing Addressee Deduction Expectation for Multi-Party Conversation Generation

Modeling multi-party conversations (MPCs) with graph neural networks has...

0 Jia-Chen Gu, et al. ∙

research

∙ 05/12/2023

Knowledge Refinement via Interaction Between Search Engines and Large Language Models

Information retrieval (IR) plays a crucial role in locating relevant res...

0 Jiazhan Feng, et al. ∙

research

∙ 05/08/2023

Augmented Large Language Models with Parametric Knowledge Guiding

Large Language Models (LLMs) have significantly advanced natural languag...

0 Ziyang Luo, et al. ∙

research

∙ 04/27/2023

Large Language Models are Strong Zero-Shot Retriever

In this work, we propose a simple method that applies a large language m...

0 Tao Shen, et al. ∙

research

∙ 04/24/2023

WizardLM: Empowering Large Language Models to Follow Complex Instructions

Training large language models (LLM) with open-domain instruction follow...

0 Can Xu, et al. ∙

research

∙ 02/06/2023

LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval

Image-text retrieval (ITR) is a task to retrieve the relevant images/tex...

0 Ziyang Luo, et al. ∙

research

∙ 12/20/2022

Fine-Grained Distillation for Long Document Retrieval

Long document retrieval aims to fetch query-relevant documents from a la...

0 Yucheng Zhou, et al. ∙

research

∙ 12/20/2022

Adam: Dense Retrieval Distillation with Adaptive Dark Examples

To improve the performance of the dual-encoder retriever, one effective ...

0 Chang Liu, et al. ∙

research

∙ 11/10/2022

MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation

Responding with multi-modal content has been recognized as an essential ...

0 Jiazhan Feng, et al. ∙

research

∙ 10/22/2022

Collaborative Reasoning on Multi-Modal Semantic Graphs for Video-Grounded Dialogue Generation

We study video-grounded dialogue generation, where a response is generat...

0 Xueliang Zhao, et al. ∙

research

∙ 08/31/2022

LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval

In large-scale retrieval, the lexicon-weighting paradigm, learning weigh...

0 Tao Shen, et al. ∙

research

∙ 08/29/2022

LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval

Retrieval models based on dense representations in semantic space have b...

0 Kai Zhang, et al. ∙

research

∙ 06/21/2022

KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Few-Shot NLP

This paper focuses on text data augmentation for few-shot NLP tasks. The...

0 Yufei Wang, et al. ∙

research

∙ 06/16/2022

Towards Robust Ranker for Text Retrieval

A ranker plays an indispensable role in the de facto 'retrieval rera...

0 Yucheng Zhou, et al. ∙

research

∙ 05/23/2022

UnifieR: A Unified Retriever for Large-Scale Retrieval

Large-scale retrieval is to recall relevant documents from a huge collec...

0 Tao Shen, et al. ∙

research

∙ 03/16/2022

TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledge

Generating natural and informative texts has been a long-standing proble...

0 Chao-Hong Tan, et al. ∙

research

∙ 03/16/2022

HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations

Recently, various response generation models for two-party conversations...

0 Jia-Chen Gu, et al. ∙

research

∙ 02/25/2022

PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks

This paper focuses on the Data Augmentation for low-resource Natural Lan...

0 Yufei Wang, et al. ∙

research

∙ 01/28/2022

PCL: Peer-Contrastive Learning with Diverse Augmentations for Unsupervised Sentence Embeddings

Learning sentence embeddings in an unsupervised manner is fundamental in...

0 Qiyu Wu, et al. ∙

research

∙ 10/01/2021

Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning

Establishing retrieval-based dialogue systems that can select appropriat...

0 Chongyang Tao, et al. ∙

research

∙ 06/03/2021

MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understanding

Recently, various neural models for multi-party conversation (MPC) have ...

0 Jia-Chen Gu, et al. ∙

research

∙ 05/27/2021

Maria: A Visual Experience Powered Conversational Agent

Arguably, the visual perception of conversational agents to the physical...

2 Zujie Liang, et al. ∙

research

∙ 05/07/2021

A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect

This study presents a large scale benchmarking on cloud based Speech-To-...

0 Binbin Xu, et al. ∙

research

∙ 08/29/2020

Zero-Resource Knowledge-Grounded Dialogue Generation

While neural conversation models have shown great potentials towards gen...

0 Linxiao Li, et al. ∙

research

∙ 04/30/2020

EnsembleGAN: Adversarial Learning for Retrieval-Generation Ensemble Model on Short-Text Conversation

Generating qualitative responses has always been a challenge for human-c...

0 Jiayi Zhang, et al. ∙

research

∙ 02/24/2020

Low-Resource Knowledge-Grounded Dialogue Generation

Responding with knowledge has been recognized as an important capability...

0 Xueliang Zhao, et al. ∙

research

∙ 06/18/2019

Mimicking Human Process: Text Representation via Latent Semantic Clustering for Classification

Considering that words with different characteristic in the text have di...

0 Xiaoye Tan, et al. ∙

research

∙ 06/14/2019

Neural Response Generation with Meta-Words

We present open domain response generation with meta-words. A meta-word ...

0 Can Xu, et al. ∙

research

∙ 06/11/2019

Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems

We study learning of a matching model for response selection in retrieva...

0 Jiazhan Feng, et al. ∙

research

∙ 06/11/2019

A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots

We present a document-grounded matching network (DGMN) for response sele...

0 Xueliang Zhao, et al. ∙

research

∙ 09/27/2018

Iterative Document Representation Learning Towards Summarization with Polishing

In this paper, we introduce Iterative Text Summarization (ITS), an itera...

0 Xiuying Chen, et al. ∙

research

∙ 08/23/2018

Playing 20 Question Game with Policy-Based Reinforcement Learning

The 20 Questions (Q20) game is a well known game which encourages deduct...

0 Huang Hu, et al. ∙

research

∙ 08/22/2018

Improving Matching Models with Contextualized Word Representations for Multi-turn Response Selection in Retrieval-based Chatbots

We consider matching with pre-trained contextualized word vectors for mu...

0 Chongyang Tao, et al. ∙

research

∙ 01/11/2017

RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

Open-domain human-computer conversation has been attracting increasing a...

0 Chongyang Tao, et al. ∙

Chongyang Tao

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