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Nested Learning: A New Machine Learning Approach for Continual Learning that Views Models as Nested Optimization Problems to Enhance Long Context Processing
How can we build AI systems that keep learning new information over time without forgetting...
NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings
arXiv:2509.04011v1 Announce Type: cross Abstract: We present NER Retriever, a zero-shot retrieval framework for ad-hoc...
Nemotron-CC-Math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset
arXiv:2508.15096v1 Announce Type: new Abstract: Pretraining large language models (LLMs) on high-quality, structured data such...
Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
arXiv:2512.20848v1 Announce Type: new Abstract: We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer...
Nebius AI Advances Open-Weight LLMs Through Reinforcement Learning for Capable SWE Agents
The landscape of software engineering automation is evolving rapidly, driven by advances in Large Language...
NDT: Non-Differential Transformer and Its Application to Sentiment Analysis
arXiv:2603.20704v1 Announce Type: cross Abstract: From customer feedback to social media, understanding human sentiment in...
Natural language processing for African languages
arXiv:2507.00297v1 Announce Type: new Abstract: Recent advances in word embeddings and language models use large-scale...
Native RAG vs. Agentic RAG: Which Approach Advances Enterprise AI Decision-Making?
Retrieval-Augmented Generation (RAG) has emerged as a cornerstone technique for enhancing Large Language Models (LLMs)...
National University of Singapore Researchers Introduce Dimple: A Discrete Diffusion Multimodal Language Model for Efficient and Controllable Text Generation
In recent months, there has been growing interest in applying diffusion models—originally designed for continuous...
NASA is building the first nuclear reactor-powered interplanetary spacecraft. How will it work?
MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to...
NAS-LoRA: Empowering Parameter-Efficient Fine-Tuning for Visual Foundation Models with Searchable Adaptation
arXiv:2512.03499v1 Announce Type: cross Abstract: The Segment Anything Model (SAM) has emerged as a powerful...
Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools
arXiv:2507.05305v1 Announce Type: cross Abstract: Frontier Large language models (LLMs) like ChatGPT and Gemini can...
