5th International Conference on NLP and Machine Learning Trends (NLMLT 2026)
Local: Melbourne, Australia
Data do evento: 15/08/2026 a 16/08/2026
Prazo de submissão de trabalhos: 07/06/2026
5thInternational Conference on NLP and Machine Learning Trends (NLMLT 2026)August 15 ~ 16, 2026,Melbourne, AustraliaScope & Topics5thInternational Conference on NLP and Machine Learning Trends (NLMLT 2026)invites high quality research contributions that advance the rapidly evolving fields of Natural Language Processing and Machine Learning. As foundation models, multimodal systems and efficient learning architectures reshape the landscape of intelligent technologies, NLMLT 2026 provides a global forum for researchers, practitioners and industry innovators to share breakthroughs discuss emerging challenges and explore the next generation of NLP and ML solutions.We welcome original research papers, survey articles, case studies and industrial applications that highlight significant progress in language technologies, learning algorithms, multimodal intelligence, efficient model design, responsible AI and real world deployment. Submissions may address theoretical foundations, methodological innovations, or practical implementations that push the boundaries of modern NLP and ML.Authors are encouraged to contribute work related to the conference topics listed below, but submissions are not limited to these areas.Topics of interest include, but are not limited to, the followingLarge Language Models, Foundation Models and In Context LearningPre training, fine tuning and instruction tuningIn context learning (ICL) and meta learningPrompt engineering, soft prompts and adaptersRetrieval Augmented Generation (RAG)Long context models and memory architecturesAlignment, RLHF, DPO and safety tuningHallucination detection and mitigationLLM security, adversarial robustness and red teamingTokenizer free and modular language modelsSynthetic data generation, validation and governanceSmall Language Models (SLMs) and Efficient ArchitecturesFocus on compact, efficient and deployable NLP/ML modelsSmall Language Models for edge and on device NLPDomain specialized compact modelsEfficient transformer alternatives (Mamba, RWKV, Hyena, S4, etc.)Sparse models and Mixture of Experts (MoE)Hardware aware optimization for NLPNLP Tasks and Advanced Language UnderstandingMachine Translation (speech to speech, low resource, multimodal)Question Answering and Reading ComprehensionSummarization (factuality aware, abstractive)Information Extraction and Named Entity RecognitionSentiment, Emotion and Intent AnalysisDialogue Systems and Conversational AIText Generation, Style Transfer and Controlled GenerationSemantic Parsing, Discourse and PragmaticsMultimodal and Multisensory AIVision Language Models (VLMs)Audio Language Models (ASR/TTS)Video Language UnderstandingMultimodal grounding and reasoningEmbodied AI and interactive multimodal agentsReasoning, Planning and Neuro Symbolic NLPMulti step reasoning and chain of thought modelingTool using LLM agents and autonomous workflowsPlanning augmented NLP systemsNeuro symbolic reasoning and hybrid modelsMathematical reasoning and theorem assisted NLPMulti agent communication and emergent behaviorMachine Learning Theory and Methods for NLPTransformer architectures and sequence modelingRepresentation learning and embeddingsSelf supervised, semi supervised and weakly supervised learningGeneralization, robustness and domain adaptationContinual, lifelong and curriculum learningProbabilistic modeling and Bayesian deep learningOptimization methods for large scale NLPEfficient, Scalable and Green NLPModel compression, pruning and distillationQuantization and low precision inferenceDistributed training and scalable optimizationEnergy efficient NLP systemsEdge NLP and on device inferenceEthics, Fairness, Safety and Responsible NLPBias detection and mitigationFairness in multilingual and low resource NLPPrivacy preserving NLP (federated, encrypted computation)Trustworthy evaluation and benchmark designSafety critical NLP applicationsAI governance, transparency and accountabilityMultilingual, Cross Lingual and Low Resource NLPCross lingual transfer learningLow resource language modelingMultilingual LLMs and translation systemsCode switching and mixed language NLPTypology aware modeling and linguistic diversitySpeech Language Unified ModelsSpeech language joint modelingSpeech to speech translationAudio text alignment and groundingSpoken dialogue systemsApplied NLP and ML SystemsHealthcare NLPLegal, financial and scientific NLPRecommender systems powered by NLPSearch, retrieval and ranking systemsEducational NLPSocial media analysis and misinformation detectionData, Resources and EvaluationDataset creation, augmentation and curationSynthetic data pipelines and validationAnnotation tools and human in the loop systemsEvaluation metrics and benchmark developmentBenchmark contamination detectionRobustness under distribution shiftPaper SubmissionAuthors are invited to submit papers through the conferenceSubmission SystembyJune 07, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published byComputer Science Conference ProceedingsinComputer Science & Information Technology (CS & IT)series (Confirmed).Selected papers fromNLMLT 2026, after further revisions, will be published in the special issue of the following journals.International Journal of Artificial Intelligence & Applications (IJAIA)Machine Learning and Applications: An International Journal (MLAIJ)International Journal of Ubiquitous Computing (IJU)Advances in Vision Computing: An International Journal (AVC)International Journal on Natural Language Computing (IJNLC)Information Technology in Industry (ITII)Important DatesSubmission Deadline:June 07, 2026Authors Notification:July 25, 2026Final Manuscript Due:August 01, 2026