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-a-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