1. Track 1: Language Analysis and Representation:
Phonetics, Phonology, and Morphology;
Syntax, Semantics, Discourse, Pragmatics, Dialogue, and Lexicon;
Word and Sentence Representation;
POS Tagging; Parsing;
Semantic Role Labelling;
Word-Sense Disambiguation;
Semantic Analysis and Representation;
Anaphora Resolution;

2. Track 2: Language Processing Models and Techniques:
Mathematical, Statistical, Machine Learning, and Deep Learning Models;
Mathematical and Statistical Models;
Machine Learning Models;
Deep Learning Models;
Pretrain Language Models;
Large Language Models;
Prompt Engineering;

Track 3: Language Resources and Tools:
Language Resources and Corpora;
Electronic Dictionaries, Terminologies, and Ontologies;
Linked Data;
Laguage Resource Construction ;
Knowledge Graph ;
Ontology Match and Merge;
Tools for langauge resources evaluation;

Track 4. Multilingual and Cross-Lingual Processing:
Multilingual NLP;
Machine Translation, Translation Memory Systems, and Computer-Aided Translation Tools;
Text Simplification and Readability Estimation;
Cross-Lingual Text Analysis and Retrieval;
 

Track 5. Information Extraction and Retrieval:
Knowledge Acquisition;
Information Retrieval;
Text Categorization; 
Information Extraction;
Text Summarization;
Terminology Extraction; 
Question Answering;
Fact Checking;

Track 6: Sentiment Analysis and Human Interaction::
Opinion Mining and Sentiment Analysis;
Stance Recognition;
Author Profiling;
Dialogue Systems;
Computer-Aided Language Learning;
 

Track 7. Specialized NLP Applications:
NLP for Biomedical Texts and Healthcare;
NLP for the Semantic Web; 
NLP for Law;
NLP for Audition;
NLP for Education;

8. Track 8: Multi-modal Information Processing: Recent advances and applications
Acquisition for Multi-Modal Data; 
Multi-Modal Representation; 
Multi-Modal Alignment and Fusion ; 
Cross-Modal Retrieval, Co-Training, Transfer Learning, Few/Zero-Shot Learning; 
Applications of Multi-Modal Information Processing;