Conference Information
ICNLP 2025: International Conference on Natural Language Processing
https://www.icnlp.net/Submission Date: |
2024-11-30 Extended |
Notification Date: |
2024-12-30 |
Conference Date: |
2025-03-21 |
Location: |
Guangzhou, China |
Years: |
7 |
Viewed: 13040 Tracked: 7 Attend: 4
Call For Papers
Topics of ICNLP 2025 include, but are not limited to, the following: 1. Language Analysis and Representation: Phonetics, Phonology, and Morphology; Syntax, Semantics, Discourse, Pragmatics, Dialogue, and Lexicon; Word and Sentence Representation; word and sentence representation; POS Tagging; Parsing; Semantic Role Labelling; Word-Sense Disambiguation; Multiword Expressions; Anaphora Resolution; 2. Language Processing Models and Techniques: Complexity; Mathematical, Statistical, Machine Learning, and Deep Learning Models; Mathematical and Statistical Models; Machine Learning Models; Deep Learning Models ; 3. Language Resources and Tools: Language Resources and Corpora; Electronic Dictionaries, Terminologies, and Ontologies; Linked Data; 4. Multilingual and Cross-Lingual Processing: Multilingual NLP; Machine Translation, Translation Memory Systems, and Computer-Aided Translation Tools; Text Simplification and Readability Estimation; 5. Information Extraction and Retrieval: Knowledge Acquisition; Information Retrieval; Text Categorization; Information Extraction; Text Summarization; Terminology Extraction; Question Answering; Fact Checking; 6. Sentiment Analysis and Human Interaction:: Opinion Mining and Sentiment Analysis; Stance Recognition; Author Profiling; Dialogue Systems; Computer-Aided Language Learning; 7. Specialized NLP Applications: NLP for Biomedical Texts and Healthcare; NLP for the Semantic Web; 8. Special Session I topics: Multi-modal Information Processing: Recent advances and applications Single Modal Data Analysis; Acquisition Techniques for Multi-Modal Data; Multi-Modal Representation and Translation; Multi-Modal Alignment and Fusion ; Cross-Modal Retrieval, Co-Training, Transfer Learning, Few/Zero-Shot Learning; Applications of Multi-Modal Information Processing;
Last updated by Dunn Carl in 2024-11-01
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