Welcome
Welcome to
AINLP 2027
The 4th International Conference on
Artificial Intelligence and Natural Language Processing
About AINLP 2027
The 4th International Conference on Artificial Intelligence and Natural Language Processing (AINLP 2027) will be held in Nanyang, Henan Province, China, from August 20 to 22, 2027. The conference focuses on the frontier intersection of artificial intelligence and natural language processing, covering hot topics such as large language models, multimodal semantic understanding, generative AI, dialogue systems, knowledge-enhanced NLP, and low-resource language processing. It aims to provide a high-level exchange platform for global scholars, researchers, and industry experts to share the latest achievements, discuss technical challenges, and explore cooperation opportunities. We sincerely invite colleagues from home and abroad to gather in Nanyang and jointly explore the future of AI and NLP.
sub&Pub
Please send the full paper (Word+PDF)
All accepted full papers will be published in the conference proceedings and will be submitted to Ei Compendex / Scopus for indexing.
Note: All submitted articles should report original research results, experimental or theoretical, not previously published or under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.
CFP
The topics of interest for submission include,
But are not limited to:
Machine Learning for NLP
Graph-based methods
Knowledge-augmented methods
Multi-task learning
Self-supervised learning
Contrastive learning
Generation model
Data augmentation
Word embedding
Structured prediction
Transfer learning / domain adaptation
Representation learning
Generalization
Model compression methods
Parameter-efficient finetuning
Few-shot learning
Reinforcement learning
Optimization methods
Continual learning
Adversarial training
Meta learning
Causality
Graphical models
Human-in-the-loop / Active learning
NLP Applications
Educational applications, GEC, essay scoring
Hate speech detection
Multimodal applications
Code generation and understanding
Fact checking, rumour/misinformation detection
Healthcare applications, clinical NLP
Financial/business NLP
Legal NLP
Mathematical NLP
Security/privacy
Historical NLP
Knowledge graph
language generation
Human evaluation
Automatic evaluation
Multilingualism
Efficient models
Few-shot generation
Analysis
Domain adaptation
Data-to-text generation
Text-to-text generation
Inference methods
Model architectures
Retrieval-augmented generation
Interactive and collaborative generation
Machine Translation
Automatic evaluation
Biases
Domain adaptation
Efficient inference for MT
Efficient MT training
Few-/Zero-shot MT
Human evaluation
Interactive MT
MT deployment and maintenance
MT theory
Modeling
Multilingual MT
Multimodality
Online adaptation for MT
Parallel decoding/non-autoregressive MT
Pre-training for MT
Scaling
Speech translation
Code-switching translation
Vocabulary learning
Interpretability and Analysis of Models in NLP
Adversarial attacks/examples/training
Calibration/uncertainty
Counterfactual/contrastive explanations
Data influence
Data shortcuts/artifacts
Explanation faithfulness
Feature attribution
Free-text/natural language explanation
Hardness of samples
Hierarchical & concept explanations
Human-subject application-grounded evaluations
Knowledge tracing/discovering/inducing
Probing
Robustness
Topic modeling
Supported by (2026)
Supported (2026)
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contact
🎓️️
Joey.Zhai
Conference Secretary
☎️
+86-17512806705 (WeChat)
📧
ICAINLP@163.com
The Secretary office of AINLP 2027 will collect contributions and handle daily organizational tasks.
All paper reviews will be completed by Program Committee Members and invited experts.
* If you have any questions or inquiries, please feel free to contact us.