5th International Conference on NLP and Machine Learning Trends

5^th International Conference on NLP and Machine Learning Trends (NLMLT 2026)

August 15 ~ 16, 2026,Melbourne, Australia

Scope & Topics

5^th International 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 following

Large Language Models, Foundation Models and In Context Learning

Pre training, fine tuning and instruction tuning
In context learning (ICL) and meta learning
Prompt engineering, soft prompts and adapters
Retrieval Augmented Generation (RAG)
Long context models and memory architectures
Alignment, RLHF, DPO and safety tuning
Hallucination detection and mitigation
LLM security, adversarial robustness and red teaming
Tokenizer free and modular language models
Synthetic data generation, validation and governance
Small Language Models (SLMs) and Efficient Architectures

Focus on compact, efficient and deployable NLP/ML models

Small Language Models for edge and on device NLP

Domain specialized compact models

Efficient transformer alternatives (Mamba, RWKV, Hyena, S4, etc.)

Sparse models and Mixture of Experts (MoE)

Hardware aware optimization for NLP

NLP Tasks and Advanced Language Understanding
Machine Translation (speech to speech, low resource, multimodal)
Question Answering and Reading Comprehension
Summarization (factuality aware, abstractive)
Information Extraction and Named Entity Recognition
Sentiment, Emotion and Intent Analysis
Dialogue Systems and Conversational AI
Text Generation, Style Transfer and Controlled Generation
Semantic Parsing, Discourse and Pragmatics
Multimodal and Multisensory AI
Vision Language Models (VLMs)
Audio Language Models (ASR/TTS)
Video Language Understanding
Multimodal grounding and reasoning
Embodied AI and interactive multimodal agents
Reasoning, Planning and Neuro Symbolic NLP
Multi step reasoning and chain of thought modeling
Tool using LLM agents and autonomous workflows
Planning augmented NLP systems
Neuro symbolic reasoning and hybrid models
Mathematical reasoning and theorem assisted NLP
Multi agent communication and emergent behavior
Machine Learning Theory and Methods for NLP
Transformer architectures and sequence modeling
Representation learning and embeddings
Self supervised, semi supervised and weakly supervised learning
Generalization, robustness and domain adaptation
Continual, lifelong and curriculum learning
Probabilistic modeling and Bayesian deep learning
Optimization methods for large scale NLP
Efficient, Scalable and Green NLP
Model compression, pruning and distillation
Quantization and low precision inference
Distributed training and scalable optimization
Energy efficient NLP systems
Edge NLP and on device inference
Ethics, Fairness, Safety and Responsible NLP
Bias detection and mitigation
Fairness in multilingual and low resource NLP
Privacy preserving NLP (federated, encrypted computation)
Trustworthy evaluation and benchmark design
Safety critical NLP applications
AI governance, transparency and accountability
Multilingual, Cross Lingual and Low Resource NLP
Cross lingual transfer learning
Low resource language modeling
Multilingual LLMs and translation systems
Code switching and mixed language NLP
Typology aware modeling and linguistic diversity
Speech Language Unified Models
Speech language joint modeling
Speech to speech translation
Audio text alignment and grounding
Spoken dialogue systems
Applied NLP and ML Systems
Healthcare NLP
Legal, financial and scientific NLP
Recommender systems powered by NLP
Search, retrieval and ranking systems
Educational NLP
Social media analysis and misinformation detection
Data, Resources and Evaluation
Dataset creation, augmentation and curation
Synthetic data pipelines and validation
Annotation tools and human in the loop systems
Evaluation metrics and benchmark development
Benchmark contamination detection
Robustness under distribution shift

Paper Submission

Authors are invited to submit papers through the conference Submission System by May 10, 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 by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from NLMLT 2026, after further revisions, will be published in the special issue of the following journals.

Important Dates

Submission Deadline	:	May 10, 2026
Authors Notification	:	June 25, 2026
Final Manuscript Due	:	July 02, 2026

Co – Located Event

***** The invited talk proposals can be submitted to nlmlt@nlmlt2026.org