Konferenzen  >  Informatik  >  Verarbeitung Natürlicher Sprache, Computerlinguistik

The British University in Dubai

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.

Tel.: [+96878476000];     Email: taher.gazal@ieee.org

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

Peking University

The Tenth International Conference on Data Mining and Big Data (DMBD'2025) serves as a global platform for researchers and practitioners to exchange the latest advancements in theories, algorithms, models, and applications of data mining, big data, and artificial intelligence techniques. Data mining involves exploring large datasets to extract meaningful information, while big data encompasses vast amounts of data and information that warrant in-depth research.

Datenbanktechlologie, Suchmaschinen und Data-Mining,    Implementierung und Anwendungen von künstlicher Intelligenz

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Speech Translation; Human Interpretation; Multilingual AI Assistant; Speech Processing; Human-Computer Interaction

Benutzerschnittstellen, User Experience, Virtuelle Realität ,    Sprachwissenschaft

European Society for the Study of English

The rapid development of AI and its integration into translator training and translation practices have led to numerous changes in both academia (Bada & Schumacher, 2024; Loock, 2025) and the translation industry (Girletti & Lefer, 2024), hence a need for trainees and professionals to adapt to an ever-changing field. The necessity of mastering new AI skills, namely prompt engineering (He, 2024: 316), leads both lecturers and professionals to reinvent themselves more than ever. Although the recent AI developments have led to the use of MT for many text types that were considered, until recently, to be AI-resistant, human intervention is still needed to maintain professional quality standards, particularly for literary translation (Hansen & Esperança-Rodier, 2022: 185), creative domains (dubbing, subtitling, localisation) (e.g. Jiménez-Crespo, 2024: 18) and specialised translation (terminology management, polysemy) (Kübler et al., 2024).