Search Results for author: Kang Liu

Found 112 papers, 30 papers with code

CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers

1 code implementation COLING 2022 Yiming Ju, Weikang Wang, Yuanzhe Zhang, Suncong Zheng, Kang Liu, Jun Zhao

To bridge the gap, we propose a new task: conditional question answering with hierarchical multi-span answers, where both the hierarchical relations and the conditions need to be extracted.

Question Answering

Knowledge Transfer with Visual Prompt in multi-modal Dialogue Understanding and Generation

no code implementations TU (COLING) 2022 Minjun Zhu, Yixuan Weng, Bin Li, Shizhu He, Kang Liu, Jun Zhao

In this work, we propose a knowledge transfer method with visual prompt (VPTG) fusing multi-modal data, which is a flexible module that can utilize the text-only seq2seq model to handle visual dialogue tasks.

Dialogue Understanding Knowledge Distillation +2

Generating Temporally-ordered Event Sequences via Event Optimal Transport

no code implementations COLING 2022 Bo Zhou, Yubo Chen, Kang Liu, Jun Zhao, Jiexin Xu, XiaoJian Jiang, Qiuxia Li

The other issue is that the model adopts a word-level objective to model events in texts, failing to evaluate the predicted results of the model from the perspective of event sequence.

Augmentation, Retrieval, Generation: Event Sequence Prediction with a Three-Stage Sequence-to-Sequence Approach

no code implementations COLING 2022 Bo Zhou, Chenhao Wang, Yubo Chen, Kang Liu, Jun Zhao, Jiexin Xu, XiaoJian Jiang, Qiuxia Li

Currently existing approach models this task as a statistical induction problem, to predict a sequence of events by exploring the similarity between the given goal and the known sequences of events.


CASIA at SemEval-2022 Task 11: Chinese Named Entity Recognition for Complex and Ambiguous Entities

no code implementations SemEval (NAACL) 2022 Jia Fu, Zhen Gan, Zhucong Li, Sirui Li, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao

This paper describes our approach to develop a complex named entity recognition system in SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, Track 9 - Chinese.

Chinese Named Entity Recognition Data Augmentation +3

Leveraging Explicit Lexico-logical Alignments in Text-to-SQL Parsing

no code implementations ACL 2022 Runxin Sun, Shizhu He, Chong Zhu, Yaohan He, Jinlong Li, Jun Zhao, Kang Liu

Text-to-SQL aims to parse natural language questions into SQL queries, which is valuable in providing an easy interface to access large databases.

SQL Parsing Text-To-SQL

CroAno : A Crowd Annotation Platform for Improving Label Consistency of Chinese NER Dataset

no code implementations EMNLP (ACL) 2021 Baoli Zhang, Zhucong Li, Zhen Gan, Yubo Chen, Jing Wan, Kang Liu, Jun Zhao, Shengping Liu, Yafei Shi

2) Inconsistency Detector: CroAno employs a detector to locate corpus-level label inconsistency and provides users an interface to correct inconsistent entities in batches.

Chinese Named Entity Recognition Management +3

Set Generation Networks for End-to-End Knowledge Base Population

no code implementations EMNLP 2021 Dianbo Sui, Chenhao Wang, Yubo Chen, Kang Liu, Jun Zhao, Wei Bi

In this paper, we formulate end-to-end KBP as a direct set generation problem, avoiding considering the order of multiple facts.

Knowledge Base Population Machine Translation

Biomedical Concept Normalization by Leveraging Hypernyms

1 code implementation EMNLP 2021 Cheng Yan, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yafei Shi, Shengping Liu

Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module.

Uncertain Local-to-Global Networks for Document-Level Event Factuality Identification

1 code implementation EMNLP 2021 Pengfei Cao, Yubo Chen, Yuqing Yang, Kang Liu, Jun Zhao

Moreover, we propose an Uncertain Information Aggregation module to leverage the global structure for integrating the local information.

Scene Restoring for Narrative Machine Reading Comprehension

no code implementations EMNLP 2020 Zhixing Tian, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yantao Jia, Zhicheng Sheng

Inspired by this behavior of humans, we propose a method to let the machine imagine a scene during reading narrative for better comprehension.

Cloze Test Machine Reading Comprehension +1

Event Extraction as Machine Reading Comprehension

no code implementations EMNLP 2020 Jian Liu, Yubo Chen, Kang Liu, Wei Bi, Xiaojiang Liu

ii) Our model is excelled in the data-scarce scenario, for example, obtaining 49. 8{\%} in F1 for event argument extraction with only 1{\%} data, compared with 2. 2{\%} of the previous method.

Event Argument Extraction Event Extraction +5

Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules

no code implementations7 Jan 2023 Yinyu Lan, Shizhu He, Kang Liu, Jun Zhao

The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs.

Knowledge Graph Embeddings Question Answering

Large Language Models are reasoners with Self-Verification

1 code implementation19 Dec 2022 Yixuan Weng, Minjun Zhu, Shizhu He, Kang Liu, Jun Zhao

We propose a new method called self-verification that uses the conclusion of the CoT as a condition to build a new sample and asks the LLM to re-predict the original conditions which be masked.

Arithmetic Reasoning Common Sense Reasoning +3

Generating Hierarchical Explanations on Text Classification Without Connecting Rules

no code implementations24 Oct 2022 Yiming Ju, Yuanzhe Zhang, Kang Liu, Jun Zhao

The opaqueness of deep NLP models has motivated the development of methods for interpreting how deep models predict.

text-classification Text Classification

PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction

no code implementations18 Oct 2022 Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang, Kang Liu, ZhiMing Ma, Wei-Ying Ma, Yanyan Lan

In our implementation, we adopt both the state-of-the-art molecule embedding models under the supervised learning paradigm and the pretraining paradigm as the molecule representation module of PEMP, respectively.

Drug Discovery Molecular Property Prediction +1

ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains

no code implementations17 Oct 2022 Minjun Zhu, Yixuan Weng, Shizhu He, Kang Liu, Jun Zhao

Recently, natural language database (NLDB) conducts complex QA in knowledge base with textual evidences rather than structured representations, this task attracts a lot of attention because of the flexibility and richness of textual evidence.

Answer Generation Question Answering +1

MEGCF: Multimodal Entity Graph Collaborative Filtering for Personalized Recommendation

1 code implementation14 Oct 2022 Kang Liu, Feng Xue, Dan Guo, Le Wu, Shujie Li, Richang Hong

This paper aims at solving the mismatch problem between MFE and UIM, so as to generate high-quality embedding representations and better model multimodal user preferences.

Collaborative Filtering Image Classification

Joint Multi-grained Popularity-aware Graph Convolution Collaborative Filtering for Recommendation

1 code implementation10 Oct 2022 Kang Liu, Feng Xue, Xiangnan He, Dan Guo, Richang Hong

In this work, we propose to model multi-grained popularity features and jointly learn them together with high-order connectivity, to match the differentiation of user preferences exhibited in popularity features.

Collaborative Filtering Recommendation Systems

Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder

1 code implementation COLING 2022 Fangyu Lei, Shizhu He, Xiang Li, Jun Zhao, Kang Liu

In the real-world question answering scenarios, hybrid form combining both tabular and textual contents has attracted more and more attention, among which numerical reasoning problem is one of the most typical and challenging problems.

Question Answering

MALICE: Manipulation Attacks on Learned Image ComprEssion

no code implementations26 May 2022 Kang Liu, Di wu, Yiru Wang, Dan Feng, Benjamin Tan, Siddharth Garg

To characterize the robustness of state-of-the-art learned image compression, we mount white-box and black-box attacks.

Image Compression Image Reconstruction

LingYi: Medical Conversational Question Answering System based on Multi-modal Knowledge Graphs

1 code implementation20 Apr 2022 Fei Xia, Bin Li, Yixuan Weng, Shizhu He, Kang Liu, Bin Sun, Shutao Li, Jun Zhao

The medical conversational system can relieve the burden of doctors and improve the efficiency of healthcare, especially during the pandemic.

Conversational Question Answering Dialogue Generation +3

Logic Traps in Evaluating Attribution Scores

no code implementations ACL 2022 Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao

Meanwhile, since the reasoning process of deep models is inaccessible, researchers design various evaluation methods to demonstrate their arguments.

Lifelong Intent Detection via Multi-Strategy Rebalancing

no code implementations10 Aug 2021 Qingbin Liu, Xiaoyan Yu, Shizhu He, Kang Liu, Jun Zhao

In this paper, we propose Lifelong Intent Detection (LID), which continually trains an ID model on new data to learn newly emerging intents while avoiding catastrophically forgetting old data.

Intent Detection Knowledge Distillation

Alignment Rationale for Natural Language Inference

1 code implementation ACL 2021 Zhongtao Jiang, Yuanzhe Zhang, Zhao Yang, Jun Zhao, Kang Liu

Deep learning models have achieved great success on the task of Natural Language Inference (NLI), though only a few attempts try to explain their behaviors.

Natural Language Inference

Document-level Event Extraction via Parallel Prediction Networks

2 code implementations ACL 2021 Hang Yang, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang

We argue that sentence-level extractors are ill-suited to the DEE task where event arguments always scatter across sentences and multiple events may co-exist in a document.

Document-level Event Extraction Event Extraction

Knowledge-Enriched Event Causality Identification via Latent Structure Induction Networks

no code implementations ACL 2021 Pengfei Cao, Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao, Yuguang Chen, Weihua Peng

Specifically, to make use of the descriptive knowledge, we devise a Descriptive Graph Induction module to obtain and encode the graph-structured descriptive knowledge.

Event Causality Identification

A Large-Scale Chinese Multimodal NER Dataset with Speech Clues

1 code implementation ACL 2021 Dianbo Sui, Zhengkun Tian, Yubo Chen, Kang Liu, Jun Zhao

In this paper, we aim to explore an uncharted territory, which is Chinese multimodal named entity recognition (NER) with both textual and acoustic contents.

named-entity-recognition Named Entity Recognition +1

LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification

no code implementations ACL 2021 Xinyu Zuo, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Weihua Peng, Yuguang Chen

On the other hand, our approach employs a dual mechanism, which is a learnable augmentation framework and can interactively adjust the generation process to generate task-related sentences.

Data Augmentation Event Causality Identification

Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion

no code implementations27 May 2021 Yinyu Lan, Shizhu He, Xiangrong Zeng, Shengping Liu, Kang Liu, Jun Zhao

To address the above issues, this paper proposes two novel path-based reasoning methods to solve the sparsity issues of entity and path respectively, which adopts the textual semantic information of entities and paths for MedKGC.

Modeling Spatial Nonstationarity via Deformable Convolutions for Deep Traffic Flow Prediction

no code implementations8 Jan 2021 Wei Zeng, Chengqiao Lin, Kang Liu, Juncong Lin, Anthony K. H. Tung

Furthermore, to better fit with convolutions, we suggest to first aggregate traffic flows according to pre-conceived regions or self-organized regions based on traffic flows, then dispose to sequentially organized raster images for network input.

Traffic Prediction

Graph-Based Knowledge Integration for Question Answering over Dialogue

no code implementations COLING 2020 Jian Liu, Dianbo Sui, Kang Liu, Jun Zhao

Despite many advances, existing approaches for this task did not consider dialogue structure and background knowledge (e. g., relationships between speakers).

Machine Reading Comprehension Question Answering +1

Joint Entity and Relation Extraction with Set Prediction Networks

1 code implementation3 Nov 2020 Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Xiangrong Zeng, Shengping Liu

Compared with cross-entropy loss that highly penalizes small shifts in triple order, the proposed bipartite matching loss is invariant to any permutation of predictions; thus, it can provide the proposed networks with a more accurate training signal by ignoring triple order and focusing on relation types and entities.

Joint Entity and Relation Extraction

KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision

no code implementations COLING 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

Modern models of event causality detection (ECD) are mainly based on supervised learning from small hand-labeled corpora.

Data Augmentation

Towards Causal Explanation Detection with Pyramid Salient-Aware Network

no code implementations CCL 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

PSAN can assist in causal explanation detection via capturing the salient semantics of discourses contained in their keywords with a bottom graph-based word-level salient network.

Event Coreference Resolution via a Multi-loss Neural Network without Using Argument Information

no code implementations22 Sep 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

Event coreference resolution(ECR) is an important task in Natural Language Processing (NLP) and nearly all the existing approaches to this task rely on event argument information.

coreference-resolution Coreference Resolution +2

Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images

no code implementations19 Sep 2020 Kang Liu, Benjamin Tan, Siddharth Garg

Unprecedented data collection and sharing have exacerbated privacy concerns and led to increasing interest in privacy-preserving tools that remove sensitive attributes from images while maintaining useful information for other tasks.

Facial Expression Recognition (FER) Privacy Preserving

Connecting Embeddings for Knowledge Graph Entity Typing

1 code implementation ACL 2020 Yu Zhao, Anxiang Zhang, Ruobing Xie, Kang Liu, Xiaojie Wang

In this paper, we propose a novel approach for KG entity typing which is trained by jointly utilizing local typing knowledge from existing entity type assertions and global triple knowledge from KGs.

Entity Typing Knowledge Graph Completion

RGCF: Refined Graph Convolution Collaborative Filtering with concise and expressive embedding

1 code implementation7 Jul 2020 Kang Liu, Feng Xue, Richang Hong

In this work, we develop a new GCN-based Collaborative Filtering model, named Refined Graph convolution Collaborative Filtering(RGCF), where the construction of the embeddings of users (items) are delicately redesigned from several aspects during the aggregation on the graph.

Collaborative Filtering

Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks

no code implementations26 Apr 2020 Kang Liu, Benjamin Tan, Gaurav Rajavendra Reddy, Siddharth Garg, Yiorgos Makris, Ramesh Karri

Deep learning (DL) offers potential improvements throughout the CAD tool-flow, one promising application being lithographic hotspot detection.

Data Augmentation

NNoculation: Catching BadNets in the Wild

1 code implementation19 Feb 2020 Akshaj Kumar Veldanda, Kang Liu, Benjamin Tan, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Brendan Dolan-Gavitt, Siddharth Garg

This paper proposes a novel two-stage defense (NNoculation) against backdoored neural networks (BadNets) that, repairs a BadNet both pre-deployment and online in response to backdoored test inputs encountered in the field.

Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots

no code implementations CONLL 2019 Cao Liu, Kang Liu, Shizhu He, Zaiqing Nie, Jun Zhao

Facing this challenge, we present a response generation model which incorporates Interlocutor-aware Contexts into Recurrent Encoder-Decoder frameworks (ICRED) for RGMPC.

Chatbot Response Generation

Copy-Enhanced Heterogeneous Information Learning for Dialogue State Tracking

no code implementations21 Aug 2019 Qingbin Liu, Shizhu He, Kang Liu, Shengping Liu, Jun Zhao

How to integrate the semantic information of pre-defined ontology and dialogue text (heterogeneous texts) to generate unknown values and improve performance becomes a severe challenge.

Dialogue State Tracking Task-Oriented Dialogue Systems

Vocabulary Pyramid Network: Multi-Pass Encoding and Decoding with Multi-Level Vocabularies for Response Generation

no code implementations ACL 2019 Cao Liu, Shizhu He, Kang Liu, Jun Zhao

To tackle the above two problems, we present a Vocabulary Pyramid Network (VPN) which is able to incorporate multi-pass encoding and decoding with multi-level vocabularies into response generation.

Response Generation

AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing

no code implementations ACL 2019 Xiang Zhang, Shizhu He, Kang Liu, Jun Zhao

To keep the model aware of the underlying grammar in target sequences, many constrained decoders were devised in a multi-stage paradigm, which decode to the sketches or abstract syntax trees first, and then decode to target semantic tokens.

Semantic Parsing

Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection

no code implementations25 Jun 2019 Kang Liu, Hao-Yu Yang, Yuzhe ma, Benjamin Tan, Bei Yu, Evangeline F. Y. Young, Ramesh Karri, Siddharth Garg

There is substantial interest in the use of machine learning (ML) based techniques throughout the electronic computer-aided design (CAD) flow, particularly those based on deep learning.

Patch alignment manifold matting

no code implementations16 Apr 2019 Xuelong. Li, Kang Liu, Yongsheng Dong, DaCheng Tao

In this paper, a manifold matting framework named Patch Alignment Manifold Matting is proposed for image matting.

Image Matting

Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms

1 code implementation EMNLP 2018 Yubo Chen, Hang Yang, Kang Liu, Jun Zhao, Yantao Jia

Traditional approaches to the task of ACE event detection primarily regard multiple events in one sentence as independent ones and recognize them separately by using sentence-level information.

Event Detection

Event Detection via Gated Multilingual Attention Mechanism

no code implementations AAAI-18 2018 Jian Liu, Yubo Chen, Kang Liu, Jun Zhao

In specific, to alleviate data scarcity problem, we exploit the consistent information in multilingual data via context attention mechanism.

Event Detection

Pattern-revising Enhanced Simple Question Answering over Knowledge Bases

no code implementations COLING 2018 Yanchao Hao, Hao liu, Shizhu He, Kang Liu, Jun Zhao

Question Answering over Knowledge Bases (KB-QA), which automatically answer natural language questions based on the facts contained by a knowledge base, is one of the most important natural language processing (NLP) tasks.

Entity Linking Fact Selection +2

Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks

3 code implementations30 May 2018 Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg

Our work provides the first step toward defenses against backdoor attacks in deep neural networks.

IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations

no code implementations IJCNLP 2017 Shangmin Guo, Kang Liu, Shizhu He, Cao Liu, Jun Zhao, Zhuoyu Wei

The IJCNLP-2017 Multi-choice Question Answering(MCQA) task aims at exploring the performance of current Question Answering(QA) techniques via the realworld complex questions collected from Chinese Senior High School Entrance Examination papers and CK12 website1.

Question Answering

Generating Natural Answers by Incorporating Copying and Retrieving Mechanisms in Sequence-to-Sequence Learning

no code implementations ACL 2017 Shizhu He, Cao Liu, Kang Liu, Jun Zhao

Generating answer with natural language sentence is very important in real-world question answering systems, which needs to obtain a right answer as well as a coherent natural response.

Question Answering

Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?

1 code implementation EACL 2017 Shangmin Guo, Xiangrong Zeng, Shizhu He, Kang Liu, Jun Zhao

As one of the most important test of China, Gaokao is designed to be difficult enough to distinguish the excellent high school students.

Information Retrieval Multiple-choice +3

Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information

no code implementations3 Jun 2016 Yuanzhe Zhang, Kang Liu, Shizhu He, Guoliang Ji, Zhanyi Liu, Hua Wu, Jun Zhao

With the rapid growth of knowledge bases (KBs) on the web, how to take full advantage of them becomes increasingly important.

Question Answering

How to Generate a Good Word Embedding?

2 code implementations20 Jul 2015 Siwei Lai, Kang Liu, Liheng Xu, Jun Zhao

We analyze three critical components of word embedding training: the model, the corpus, and the training parameters.

Word Embeddings

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