ACLing2025 — 7th International Conference on AI in Computational Linguistics

The AI in Computational Linguistics (ACLing) conference serves as a premier international platform for the dissemination of cutting-edge research at the intersection of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). In light of rapid advancements in neural networks and large language models, the conference aims to foster scholarly exchange and collaboration among leading academics, researchers, and industry professionals engaged in the development and application of AI-driven methods in computational linguistics. ACLing welcomes high-quality contributions that address theoretical foundations, novel algorithms, and practical implementations across all dimensions of AI and ML in language technologies. The conference seeks to promote dialogue on emerging trends, innovative solutions, and critical challenges in the field, reflecting the growing importance and societal impact of AI-powered language processing. This year, the conference will be hosted by The British University in Dubai (BUiD), an institution recognized for its dedication to academic excellence, impactful research, and global engagement. BUiD’s commitment to fostering interdisciplinary innovation makes it an ideal venue for this prestigious event.

Topics: Advanced Information Retrieval and Question Answering, Knowledge and Information Extraction, Linguistic Theories and Formal Resources for AI, Statistical and Neural Language Modeling, Speech Technologies and Multimodal Language Interfaces, Machine Translation and Cross-Lingual NLP, Multilinguality, Code-Switching, and Low-Resource Languages, Domain-Specific NLP (e.g., Legal, Biomedical, Scientific, Educational), Syntactic Analysis, Tagging, and Parsing, Semantics, Pragmatics, and Commonsense Reasoning, Emotion Recognition, Sentiment Analysis, and Social Signal Processing, NLP for Social Media and Computational Social Science, Conversational AI, Spoken Dialogue, and Interactive Systems, Abstractive and Extractive Text Summarization, Natural Language Generation, Storytelling, and Creative AI, Text Classification, Topic Modeling, and Document Understanding, Text Mining and Large-Scale Knowledge Discovery, Vision-Language Models and Multimodal AI, Ethical, Legal, and Societal Implications of AI in Language Technologies, Large Language Models (LLMs): Architecture, Optimization, and Applications, Responsible and Interpretable AI for Language Understanding, Generative AI: Models, Evaluation, and Emerging Applications, Reinforcement Learning and Prompt Engineering for NLP Tasks, AI for Resource-Poor and Endangered Languages, Human-Centered NLP and User-Aware Language Interfaces, Benchmarking, Evaluation Metrics, and Explainability in NLP, AI-Augmented Writing, Reading, and Translation Tools