We invite submissions of original research articles, case studies, and review papers on the topics related to Artificial Intelligence and Natural Language Processing for the International Conference on Artificial Intelligence and Natural Language Processing. The conference aims to bring together researchers, engineers, and practitioners from around the world to exchange ideas and present the latest research advancements in the field.
Track1: 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-a-loop / Active learning
Track 2: 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
Track 3: 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
Track 4: 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
Track 5: 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
All submitted papers will be reviewed by at least two independent reviewers for quality, originality, relevance, and clarity.
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2025 2nd International Conference on Artificial Intelligence and Natural Language Processing (AINLP)