Kang Liu

Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network

2019

Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Temporal Relation Extraction with Joint Semantic and Syntactic Attention

2022 · Computational Intelligence and Neuroscience

Determining the temporal relationship between events has always been a challenging natural language understanding task. Previous research mainly relies on neural networks to learn effective features or artificial language features to extract temporal relationships, which …

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

2020 · arXiv (Cornell University)

Graph Convolution Network (GCN) has attracted significant attention and become the most popular method for learning graph representations. In recent years, many efforts have been focused on integrating GCN into the recommender tasks and have …

Optimal Linear Multilateration Combined With the Kalman Filter for Range-Only Tracking

2023 · IEEE Sensors Journal

This article presents the optimal estimation for the extensively concerned linear multilateral positioning issues and further improves the accuracy of range-only tracking significantly. The traditional linear multilateration method has been used to achieve target positioning …

Chinese Lexical Substitution: Dataset and Method

2023

Existing lexical substitution (LS) benchmarks were collected by asking human annotators to think of substitutes from memory, resulting in benchmarks with limited coverage and relatively small scales. To overcome this problem, we propose a novel …

Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning

2024

Jiachun Li, Pengfei Cao, Chenhao Wang, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.

REDGCN: Rating-Oriented Explicit Disentangling Graph Convolution Network for Review-Aware Recommendation

2024 · IEEE Transactions on Computational Social Systems

Rating prediction is a challenging task in review-aware recommendation. Although current methods effectively combine collaborative signals with review data, they fail to differentiate user preferences across various ratings and overlook the independence between these ratings. …

Neural-Symbolic Collaborative Distillation: Advancing Small Language Models for Complex Reasoning Tasks

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we propose Neural-Symbolic Collaborative Distillation (NesyCD), a novel knowledge distillation method for learning the complex reasoning abilities of Large Language Models (LLMs, e.g., \textgreater 13B). We argue that complex reasoning tasks are …

Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks

2015

Two problems arise when using distant supervision for relation extraction. First, in this method, an already existing knowledge base is heuristically aligned to texts, and the alignment results are treated as labeled data. However, the …

Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

Distant supervision for relation extraction is an efficient method to scale relation extraction to very large corpora which contains thousands of relations. However, the existing approaches have flaws on selecting valid instances and lack of …

An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge

2017

With the rapid growth of knowledge bases (KBs) on the web, how to take full advantage of them becomes increasingly important. Question answering over knowledge base (KB-QA) is one of the promising approaches to access …

Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms

2017

This paper tackles the task of event detection (ED), which involves identifying and categorizing events. We argue that arguments provide significant clues to this task, but they are either completely ignored or exploited in an …

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

2017

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.

Large Scaled Relation Extraction With Reinforcement Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Sentence relation extraction aims to extract relational facts from sentences, which is an important task in natural language processing field. Previous models rely on the manually labeled supervised dataset. However, the human annotation is costly …

Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism

2018

The relational facts in sentences are often complicated. Different relational triplets may have overlaps in a sentence. We divided the sentences into three types according to triplet overlap degree, including Normal, EntityPairOverlap and SingleEn-tiyOverlap. Existing …

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

2018

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. However, events in one sentence are usually interdependent …

Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism

2018

Named entity recognition (NER) is an important task in natural language processing area, which needs to determine entities boundaries and classify them into pre-defined categories. For Chinese NER task, there is only a very small …

Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning

2019

Xiangrong Zeng, Shizhu He, Daojian Zeng, Kang Liu, Shengping Liu, Jun Zhao. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). …

Event Extraction as Machine Reading Comprehension

2020

Event extraction (EE) is a crucial information extraction task that aims to extract event information in texts. Previous methods for EE typically model it as a classification task, which are data-hungry and suffer from the …