Search Results for author: Buzhou Tang

Found 27 papers, 8 papers with code

HITSZ-ICRC: A Report for SMM4H Shared Task 2020-Automatic Classification of Medications and Adverse Effect in Tweets

no code implementations SMM4H (COLING) 2020 Xiaoyu Zhao, Ying Xiong, Buzhou Tang

This is the system description of the Harbin Institute of Technology Shenzhen (HITSZ) team for the first and second subtasks of the fifth Social Media Mining for Health Applications (SMM4H) shared task in 2020.

Classification Task 2

Advancing Biomedical Text Mining with Community Challenges

no code implementations7 Mar 2024 Hui Zong, Rongrong Wu, Jiaxue Cha, Erman Wu, Jiakun Li, Liang Tao, Zuofeng Li, Buzhou Tang, Bairong Shen

In this article, we review the recent advances in community challenges specific to Chinese biomedical text mining.

Attribute Attribute Extraction +12

Toward Robust Multimodal Learning using Multimodal Foundational Models

no code implementations20 Jan 2024 Xianbing Zhao, Soujanya Poria, Xuejiao Li, Yixin Chen, Buzhou Tang

Recently, CLIP-based multimodal foundational models have demonstrated impressive performance on numerous multimodal tasks by learning the aligned cross-modal semantics of image and text pairs, but the multimodal foundational models are also unable to directly address scenarios involving modality absence.

Multimodal Sentiment Analysis

Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion

no code implementations4 Jan 2024 Shangyu Wu, Ying Xiong, Yufei Cui, Xue Liu, Buzhou Tang, Tei-Wei Kuo, Chun Jason Xue

Retrieval-based augmentations that aim to incorporate knowledge from an external database into language models have achieved great success in various knowledge-intensive (KI) tasks, such as question-answering and text generation.

Natural Language Understanding Neural Architecture Search +5

Overview of the PromptCBLUE Shared Task in CHIP2023

1 code implementation29 Dec 2023 Wei Zhu, Xiaoling Wang, Mosha Chen, Buzhou Tang

Many teams from both the industry and academia participated in the shared tasks, and the top teams achieved amazing test results.

In-Context Learning

PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain

1 code implementation22 Oct 2023 Wei Zhu, Xiaoling Wang, Huanran Zheng, Mosha Chen, Buzhou Tang

Biomedical language understanding benchmarks are the driving forces for artificial intelligence applications with large language model (LLM) back-ends.

Dialogue Generation Dialogue Understanding +6

SHAPE: A Sample-adaptive Hierarchical Prediction Network for Medication Recommendation

1 code implementation9 Sep 2023 Sicen Liu, Xiaolong Wang, Jingcheng Du, Yongshuai Hou, Xianbing Zhao, Hui Xu, Hui Wang, Yang Xiang, Buzhou Tang

Effectively medication recommendation with complex multimorbidity conditions is a critical task in healthcare.

Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences?

1 code implementation1 Jun 2023 Yuxin He, Jingyue Hu, Buzhou Tang

Under this framework, we experiment with 3 different training-inference schemes on 4 datasets (ACE05, RAMS, WikiEvents and MLEE) and discover that via training the model to extract all events in parallel, it can better distinguish the semantic boundary of each event and its ability to extract single event gets substantially improved.

Event Argument Extraction Event Extraction

SetGNER: General Named Entity Recognition as Entity Set Generation

1 code implementation Empirical Methods in Natural Language Processing 2022 Yuxin He, Buzhou Tang

Distinguished from the set-prediction NER framework, our method treats each entity as a sequence and is capable of recognizing discontinuous mentions.

named-entity-recognition Named Entity Recognition +2

CATNet: Cross-event Attention-based Time-aware Network for Medical Event Prediction

no code implementations29 Apr 2022 Sicen Liu, Xiaolong Wang, Yang Xiang, Hui Xu, Hui Wang, Buzhou Tang

It is a time-aware, event-aware and task-adaptive method with the following advantages: 1) modeling heterogeneous information and temporal information in a unified way and considering temporal irregular characteristics locally and globally respectively, 2) taking full advantage of correlations among different types of events via cross-event attention.

Time Series Analysis

Multimodal data matters: language model pre-training over structured and unstructured electronic health records

1 code implementation25 Jan 2022 Sicen Liu, Xiaolong Wang, Yongshuai Hou, Ge Li, Hui Wang, Hui Xu, Yang Xiang, Buzhou Tang

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain.

Decision Making Language Modelling +1

Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search

no code implementations30 Jul 2021 Haokui Zhang, Buzhou Tang, Wenze Hu, Xiaoyu Wang

Specifically, based on transformer, we propose a new network structure to compress the feature into a low dimensional space, and an inhomogeneous neighborhood relationship preserving (INRP) loss that aims to maintain high search accuracy.

Feature Compression Information Retrieval +2

Decomposing Word Embedding with the Capsule Network

no code implementations7 Apr 2020 Xin Liu, Qingcai Chen, Yan Liu, Joanna Siebert, Baotian Hu, Xiang-Ping Wu, Buzhou Tang

We propose a Capsule network-based method to Decompose the unsupervised word Embedding of an ambiguous word into context specific Sense embedding, called CapsDecE2S.

Binary Classification Word Embeddings +1

A Deep Learning-Based System for PharmaCoNER

no code implementations WS 2019 Ying Xiong, Yedan Shen, Yuanhang Huang, Shuai Chen, Buzhou Tang, Xiaolong Wang, Qingcai Chen, Jun Yan, Yi Zhou

The Biological Text Mining Unit at BSC and CNIO organized the first shared task on chemical {\&} drug mention recognition from Spanish medical texts called PharmaCoNER (Pharmacological Substances, Compounds and proteins and Named Entity Recognition track) in 2019, which includes two tracks: one for NER offset and entity classification (track 1) and the other one for concept indexing (track 2).

General Classification named-entity-recognition +2

Trigger Word Detection and Thematic Role Identification via BERT and Multitask Learning

no code implementations WS 2019 Dongfang Li, Ying Xiong, Baotian Hu, Hanyang Du, Buzhou Tang, Qingcai Chen

In this paper, we present our approaches for trigger word detection (task 1) and the identification of its thematic role (task 2) in AGAC track of BioNLP Open Shared Task 2019.

Drug Discovery Multi-Task Learning +3

HITSZ-ICRC: A Report for SMM4H Shared Task 2019-Automatic Classification and Extraction of Adverse Effect Mentions in Tweets

no code implementations WS 2019 Shuai Chen, Yuanhang Huang, Xiaowei Huang, Haoming Qin, Jun Yan, Buzhou Tang

This is the system description of the Harbin Institute of Technology Shenzhen (HITSZ) team for the first and second subtasks of the fourth Social Media Mining for Health Applications (SMM4H) shared task in 2019.

The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification

no code implementations EMNLP 2018 Jing Chen, Qingcai Chen, Xin Liu, Haijun Yang, Daohe Lu, Buzhou Tang

As the largest manually annotated public Chinese SSEI corpus in the bank domain, the BQ corpus is not only useful for Chinese question semantic matching research, but also a significant resource for cross-lingual and cross-domain SSEI research.

Clustering Paraphrase Identification +2

LCQMC:A Large-scale Chinese Question Matching Corpus

no code implementations COLING 2018 Xin Liu, Qingcai Chen, Chong Deng, Huajun Zeng, Jing Chen, Dongfang Li, Buzhou Tang

In this paper, we first use a search engine to collect large-scale question pairs related to high-frequency words from various domains, then filter irrelevant pairs by the Wasserstein distance, and finally recruit three annotators to manually check the left pairs.

Information Retrieval Machine Translation +3

Incorporating Label Dependency for Answer Quality Tagging in Community Question Answering via CNN-LSTM-CRF

1 code implementation COLING 2016 Yang Xiang, Xiaoqiang Zhou, Qingcai Chen, Zhihui Zheng, Buzhou Tang, Xiaolong Wang, Yang Qin

In community question answering (cQA), the quality of answers are determined by the matching degree between question-answer pairs and the correlation among the answers.

Community Question Answering

Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering

no code implementations IJCNLP 2015 Xiaoqiang Zhou, Baotian Hu, Qingcai Chen, Buzhou Tang, Xiaolong Wang

In this paper, the answer selection problem in community question answering (CQA) is regarded as an answer sequence labeling task, and a novel approach is proposed based on the recurrent architecture for this problem.

Answer Selection Community Question Answering

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