Titlebook: Natural Language Processing and Chinese Computing; 13th National CCF Co Derek F. Wong,Zhongyu Wei,Muyun Yang Conference proceedings 2025 Th

沙漠

0302-9743 NLP; Machine Translation and Multilinguality; Multi-modality and Explainability; NLP Applications and Text Mining; Sentiment Analysis, Argumentation Mining, and Social Media; Summarization and Generation..978-981-97-9442-3978-981-97-9443-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

懸掛

以煙熏消毒

CETA: Context-Enhanced and Target-Aware Hateful Meme Inference Methodw that our approach outperforms the state-of-the-art baselines on two hateful meme datasets, achieving up to 1.82% improvement in accuracy, significantly enhancing model inference and detection performance.

有危險(xiǎn)

Overview of?the?NLPCC 2024 Shared Task 3: Dialogue-Level Coreference Resolution and?Relation Extractce information and extract relations using coreference information. We describe the participating systems and their results to show the up-to-date progress in the DRE and DCR tasks, providing guidelines for future research.

Dislocation

Enhanced Nominal Compound Chain Extraction with?Boundary and?Chain Information of the predicted nominal compound chain. Experimental results show the efficiency of the information-enhanced approach in the NCCE task. Such method can also be applied in complex scenario NC recognition tasks, e.g., domain-specific NC recognition or loanword recognition.

conifer

Overview of?the?NLPCC 2024 Shared Task on?Chinese Metaphor GenerationVEHICLEs from a metaphorical sentence. This component requires the identification of the most fitting metaphor elements that correspond to the specified grounds. In addition to overall results, we report on the setup and insights from the metaphor generation shared task, which attracted a total of 4 participating teams across both subtasks.

事物的方面

EmoCRT: An Emotion-Cause Relation Enhanced Model for?Causal Emotion Entailmenting four emotion-cause relation types. The experimental results on the RECCON dataset show that the proposed model outperforms the benchmark model by 1.41% in terms of Macro-F1. In addition, we reveal the defects of the large language model (LLM) on this task.

古老

昏迷狀態(tài)

Improving Inference via?Rich Path Information for?Dialogue Relation Extractionter-sentence entity pair associations, incorporates multiple entity pair information to enrich path semantics, and employs attention mechanism to capture the semantics associated with each relation in the path information. These enhancements lead to improved inter-sentence inference and increase the effectiveness of dialogue relation extraction.

燕麥

Conference proceedings 2025nd Knowledge Graph; Information Retrieval, Dialogue Systems, and Question Answering; Large Language Models and Agents; Machine Learning for NLP; Machine Translation and Multilinguality; Multi-modality and Explainability; NLP Applications and Text Mining; Sentiment Analysis, Argumentation Mining, and Social Media; Summarization and Generation..