Search Results for author: Wentao Ma

Found 19 papers, 8 papers with code

Self-Explanation Prompting Improves Dialogue Understanding in Large Language Models

no code implementations22 Sep 2023 Haoyu Gao, Ting-En Lin, Hangyu Li, Min Yang, Yuchuan Wu, Wentao Ma, Yongbin Li

Task-oriented dialogue (TOD) systems facilitate users in executing various activities via multi-turn dialogues, but Large Language Models (LLMs) often struggle to comprehend these intricate contexts.

Dialogue Understanding

UniPCM: Universal Pre-trained Conversation Model with Task-aware Automatic Prompt

no code implementations20 Sep 2023 Yucheng Cai, Wentao Ma, Yuchuan Wu, Shuzheng Si, Yuan Shao, Zhijian Ou, Yongbin Li

Using the high-quality prompts generated, we scale the corpus of the pre-trained conversation model to 122 datasets from 15 dialog-related tasks, resulting in Universal Pre-trained Conversation Model (UniPCM), a powerful foundation model for various conversational tasks and different dialog systems.

SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents

no code implementations22 May 2023 Shuzheng Si, Wentao Ma, Haoyu Gao, Yuchuan Wu, Ting-En Lin, Yinpei Dai, Hangyu Li, Rui Yan, Fei Huang, Yongbin Li

SpokenWOZ further incorporates common spoken characteristics such as word-by-word processing and reasoning in spoken language.

Speech-Text Dialog Pre-training for Spoken Dialog Understanding with Explicit Cross-Modal Alignment

1 code implementation19 May 2023 Tianshu Yu, Haoyu Gao, Ting-En Lin, Min Yang, Yuchuan Wu, Wentao Ma, Chao Wang, Fei Huang, Yongbin Li

In this paper, we propose Speech-text dialog Pre-training for spoken dialog understanding with ExpliCiT cRoss-Modal Alignment (SPECTRA), which is the first-ever speech-text dialog pre-training model.

Emotion Recognition in Conversation Multimodal Intent Recognition +1

Gate Recurrent Unit Network based on Hilbert-Schmidt Independence Criterion for State-of-Health Estimation

no code implementations16 Mar 2023 Ziyue Huang, Lujuan Dang, Yuqing Xie, Wentao Ma, Badong Chen

State-of-health (SOH) estimation is a key step in ensuring the safe and reliable operation of batteries.

CharBERT: Character-aware Pre-trained Language Model

1 code implementation COLING 2020 Wentao Ma, Yiming Cui, Chenglei Si, Ting Liu, Shijin Wang, Guoping Hu

Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almost avoidable.

Language Modelling Question Answering +3

Benchmarking Robustness of Machine Reading Comprehension Models

1 code implementation Findings (ACL) 2021 Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma, Ting Liu, Shijin Wang

To fill this important gap, we construct AdvRACE (Adversarial RACE), a new model-agnostic benchmark for evaluating the robustness of MRC models under four different types of adversarial attacks, including our novel distractor extraction and generation attacks.

Benchmarking Machine Reading Comprehension +1

A Sentence Cloze Dataset for Chinese Machine Reading Comprehension

1 code implementation COLING 2020 Yiming Cui, Ting Liu, Ziqing Yang, Zhipeng Chen, Wentao Ma, Wanxiang Che, Shijin Wang, Guoping Hu

To add diversity in this area, in this paper, we propose a new task called Sentence Cloze-style Machine Reading Comprehension (SC-MRC).

Machine Reading Comprehension

CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension

no code implementations19 Dec 2019 Xingyi Duan, Baoxin Wang, Ziyue Wang, Wentao Ma, Yiming Cui, Dayong Wu, Shijin Wang, Ting Liu, Tianxiang Huo, Zhen Hu, Heng Wang, Zhiyuan Liu

We present a Chinese judicial reading comprehension (CJRC) dataset which contains approximately 10K documents and almost 50K questions with answers.

Machine Reading Comprehension

Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions

no code implementations21 Nov 2018 Zhipeng Chen, Yiming Cui, Wentao Ma, Shijin Wang, Guoping Hu

Machine Reading Comprehension (MRC) with multiple-choice questions requires the machine to read given passage and select the correct answer among several candidates.

Machine Reading Comprehension Multiple-choice

HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension

no code implementations15 Mar 2018 Zhipeng Chen, Yiming Cui, Wentao Ma, Shijin Wang, Ting Liu, Guoping Hu

This paper describes the system which got the state-of-the-art results at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge.

Multiple-choice Reading Comprehension

Bias-Compensated Normalized Maximum Correntropy Criterion Algorithm for System Identification with Noisy Input

no code implementations23 Nov 2017 Wentao Ma, Dongqiao Zheng, Yuanhao Li, ZhiYu Zhang, Badong Chen

This paper proposed a bias-compensated normalized maximum correntropy criterion (BCNMCC) algorithm charactered by its low steady-state misalignment for system identification with noisy input in an impulsive output noise environment.

Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation

no code implementations8 Aug 2015 Wentao Ma, Badong Chen, Jiandong Duan, Haiquan Zhao

Robust diffusion adaptive estimation algorithms based on the maximum correntropy criterion (MCC), including adaptation to combination MCC and combination to adaptation MCC, are developed to deal with the distributed estimation over network in impulsive (long-tailed) noise environments.

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