1 citations · 2 across the 9 of their papers we have counts for
9 papers
Cross-Document Cross-Lingual NLI via RST-Enhanced Graph Fusion and Interpretability Prediction
Mengying Yuan, Wenhao Wang, Zixuan Wang +5
Natural Language Inference (NLI) is a fundamental task in natural language processing. While NLI has developed many sub-directions such as sentence-level NLI, document-level NLI an…
Generative Sentiment Analysis via Latent Category Distribution and Constrained Decoding
Jun Zhou, Dongyang Yu, Kamran Aziz +4
Fine-grained sentiment analysis involves extracting and organizing sentiment elements from textual data. However, existing approaches often overlook issues of category semantic inc…
Revisiting Structured Sentiment Analysis as Latent Dependency Graph Parsing
Chengjie Zhou, Bobo Li, Hao Fei +3
Structured Sentiment Analysis (SSA) was cast as a problem of bi-lexical dependency graph parsing by prior studies. Multiple formulations have been proposed to construct the graph,…
Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm
Qiang Gao, Zixiang Meng, Bobo Li +4
Document-level event extraction aims to extract structured event information from unstructured text. However, a single document often contains limited event information and the rol…
Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information
Qiang Gao, Bobo Li, Zixiang Meng +5
Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such…
Modeling Unified Semantic Discourse Structure for High-quality Headline Generation
Minghui Xu, Hao Fei, Fei Li +4
Headline generation aims to summarize a long document with a short, catchy title that reflects the main idea. This requires accurately capturing the core document semantics, which…
CMNER: A Chinese Multimodal NER Dataset based on Social Media
Yuanze Ji, Bobo Li, Jun Zhou +3
Multimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of da…
Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought
Li Zheng, Hao Fei, Fei Li +4
With the proliferation of dialogic data across the Internet, the Dialogue Commonsense Multi-choice Question Answering (DC-MCQ) task has emerged as a response to the challenge of co…
Compositional Generalization for Multi-label Text Classification: A Data-Augmentation Approach
Yuyang Chai, Zhuang Li, Jiahui Liu +4
Despite significant advancements in multi-label text classification, the ability of existing models to generalize to novel and seldom-encountered complex concepts, which are compos…