Search Results for author: Zhixu Li

Found 24 papers, 13 papers with code

Tackling Zero Pronoun Resolution and Non-Zero Coreference Resolution Jointly

1 code implementation CoNLL (EMNLP) 2021 Shisong Chen, Binbin Gu, Jianfeng Qu, Zhixu Li, An Liu, Lei Zhao, Zhigang Chen

Zero pronoun resolution aims at recognizing dropped pronouns and pointing out their anaphoric mentions, while non-zero coreference resolution targets at clustering mentions referring to the same entity.


AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities

1 code implementation9 Aug 2023 Jingdan Zhang, Jiaan Wang, Xiaodan Wang, Zhixu Li, Yanghua Xiao

Multi-modal knowledge graphs (MMKGs) combine different modal data (e. g., text and image) for a comprehensive understanding of entities.

Extract Aspect Image Retrieval +2

Go Beyond The Obvious: Probing the gap of INFORMAL reasoning ability between Humanity and LLMs by Detective Reasoning Puzzle Benchmark

no code implementations11 Jul 2023 Zhouhon Gu, Zihan Li, Lin Zhang, Zhuozhi Xiong, Haoning Ye, Yikai Zhang, Wenhao Huang, Xiaoxuan Zhu, Qianyu He, Rui Xu, Sihang Jiang, Shusen Wang, Zili Wang, Hongwei Feng, Zhixu Li, Yanghua Xiao

Informal reasoning ability is the ability to reason based on common sense, experience, and intuition. Humans use informal reasoning every day to extract the most influential elements for their decision-making from a large amount of life-like information. With the rapid development of language models, the realization of general artificial intelligence has emerged with hope.

Common Sense Reasoning Decision Making +1

Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model

no code implementations17 Jun 2023 Jiaan Wang, Jianfeng Qu, Yunlong Liang, Zhixu Li, An Liu, Guanfeng Liu, Xin Zheng

Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence.

Knowledge Graphs

Towards Unifying Multi-Lingual and Cross-Lingual Summarization

no code implementations16 May 2023 Jiaan Wang, Fandong Meng, Duo Zheng, Yunlong Liang, Zhixu Li, Jianfeng Qu, Jie zhou

In this paper, we aim to unify MLS and CLS into a more general setting, i. e., many-to-many summarization (M2MS), where a single model could process documents in any language and generate their summaries also in any language.

Language Modelling Text Summarization

GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation

no code implementations25 Mar 2023 Zhouhong Gu, Sihang Jiang, Jingping Liu, Yanghua Xiao, Hongwei Feng, Zhixu Li, Jiaqing Liang, Jian Zhong

The previous methods suffer from low-efficiency since they waste much time when most of the new coming concepts are indeed noisy concepts.

Taxonomy Expansion

Is ChatGPT a Good NLG Evaluator? A Preliminary Study

1 code implementation7 Mar 2023 Jiaan Wang, Yunlong Liang, Fandong Meng, Zengkui Sun, Haoxiang Shi, Zhixu Li, Jinan Xu, Jianfeng Qu, Jie zhou

In detail, we regard ChatGPT as a human evaluator and give task-specific (e. g., summarization) and aspect-specific (e. g., relevance) instruction to prompt ChatGPT to evaluate the generated results of NLG models.

Story Generation

Zero-Shot Cross-Lingual Summarization via Large Language Models

no code implementations28 Feb 2023 Jiaan Wang, Yunlong Liang, Fandong Meng, Beiqi Zou, Zhixu Li, Jianfeng Qu, Jie zhou

Given a document in a source language, cross-lingual summarization (CLS) aims to generate a summary in a different target language.


Understanding Translationese in Cross-Lingual Summarization

no code implementations14 Dec 2022 Jiaan Wang, Fandong Meng, Tingyi Zhang, Yunlong Liang, Jiarong Xu, Zhixu Li, Jie zhou

Given a document in a source language, cross-lingual summarization (CLS) aims at generating a concise summary in a different target language.

Long-Document Cross-Lingual Summarization

1 code implementation1 Dec 2022 Shaohui Zheng, Zhixu Li, Jiaan Wang, Jianfeng Qu, An Liu, Lei Zhao, Zhigang Chen

Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language.

Machine Translation

Generative Entity Typing with Curriculum Learning

1 code implementation6 Oct 2022 Siyu Yuan, Deqing Yang, Jiaqing Liang, Zhixu Li, Jinxi Liu, Jingyue Huang, Yanghua Xiao

To overcome these drawbacks, we propose a novel generative entity typing (GET) paradigm: given a text with an entity mention, the multiple types for the role that the entity plays in the text are generated with a pre-trained language model (PLM).

Entity Typing Language Modelling

RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation

1 code implementation17 Jul 2022 Kexin Wang, Zhixu Li, Jiaan Wang, Jianfeng Qu, Ying He, An Liu, Lei Zhao

Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.

Dialogue Generation Knowledge Graphs +1

WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Types

2 code implementations ACL 2022 Xuwu Wang, Junfeng Tian, Min Gui, Zhixu Li, Rui Wang, Ming Yan, Lihan Chen, Yanghua Xiao

In this paper, we present WikiDiverse, a high-quality human-annotated MEL dataset with diversified contextual topics and entity types from Wikinews, which uses Wikipedia as the corresponding knowledge base.

Entity Linking

A Survey on Cross-Lingual Summarization

no code implementations23 Mar 2022 Jiaan Wang, Fandong Meng, Duo Zheng, Yunlong Liang, Zhixu Li, Jianfeng Qu, Jie zhou

Cross-lingual summarization is the task of generating a summary in one language (e. g., English) for the given document(s) in a different language (e. g., Chinese).

Can Pre-trained Language Models Interpret Similes as Smart as Human?

1 code implementation ACL 2022 Qianyu He, Sijie Cheng, Zhixu Li, Rui Xie, Yanghua Xiao

In this paper, we investigate the ability of PLMs in simile interpretation by designing a novel task named Simile Property Probing, i. e., to let the PLMs infer the shared properties of similes.

Sentiment Analysis Sentiment Classification

Multi-Modal Knowledge Graph Construction and Application: A Survey

no code implementations11 Feb 2022 Xiangru Zhu, Zhixu Li, Xiaodan Wang, Xueyao Jiang, Penglei Sun, Xuwu Wang, Yanghua Xiao, Nicholas Jing Yuan

In this survey on MMKGs constructed by texts and images, we first give definitions of MMKGs, followed with the preliminaries on multi-modal tasks and techniques.

graph construction Knowledge Graphs +1

ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization

2 code implementations11 Feb 2022 Jiaan Wang, Fandong Meng, Ziyao Lu, Duo Zheng, Zhixu Li, Jianfeng Qu, Jie zhou

We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents.

Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks

1 code implementation29 Jan 2022 Jiaan Wang, Beiqi Zou, Zhixu Li, Jianfeng Qu, Pengpeng Zhao, An Liu, Lei Zhao

Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context.

Multi-Task Learning

Knowledge Enhanced Sports Game Summarization

1 code implementation24 Nov 2021 Jiaan Wang, Zhixu Li, Tingyi Zhang, Duo Zheng, Jianfeng Qu, An Liu, Lei Zhao, Zhigang Chen

Additionally, we also introduce a knowledge-enhanced summarizer that utilizes both live commentaries and the knowledge to generate sports news.

Multi-Modal Chorus Recognition for Improving Song Search

1 code implementation27 Jun 2021 Jiaan Wang, Zhixu Li, Binbin Gu, Tingyi Zhang, Qingsheng Liu, Zhigang Chen

In addition, our approach also helps to improve the accuracy of its downstream task - song search by more than 10. 6%.

Overcoming Data Sparsity in Group Recommendation

no code implementations2 Oct 2020 Hongzhi Yin, Qinyong Wang, Kai Zheng, Zhixu Li, Xiaofang Zhou

Specifically, we first extend BGEM to model group-item interactions, and then in order to overcome the limitation and sparsity of the interaction data generated by occasional groups, we propose a self-attentive mechanism to represent groups based on the group members.

Decision Making Graph Embedding +2

Where to Go Next: A Spatio-temporal LSTM model for Next POI Recommendation

no code implementations18 Jun 2018 Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Zhixu Li, Jiajie Xu, Victor S. Sheng

Furthermore, to reduce the number of parameters and improve efficiency, we further integrate coupled input and forget gates with our proposed model.

Sequential Recommendation

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