LLM research
Model-First Reasoning: A New Approach to Cut LLM Hallucinations
New research introduces explicit problem modeling for LLM agents, offering a structured approach to reduce hallucinations and improve reasoning reliability in AI systems.
LLM research
New research introduces explicit problem modeling for LLM agents, offering a structured approach to reduce hallucinations and improve reasoning reliability in AI systems.
LLM research
New research introduces ReflCtrl, a method for controlling when large language models engage in extended reasoning by manipulating internal representations rather than prompts.
AI Research
New arXiv research argues mathematics and coding benchmarks provide universal standards for evaluating AI capabilities, with implications for how we measure progress across all AI domains.
LLM
New research explores AI-powered annotation pipelines that combine human expertise with AI assistance to improve LLM stability and reliability through synergistic data labeling approaches.
LLM research
Researchers propose a novel approach to train LLMs to automatically identify and extract relevant context, improving inference efficiency and accuracy in long-context scenarios.
deep learning
New research demonstrates that deep neural networks exhibit phase transitions during training, revealing hierarchical feature organization that could reshape how we understand and design AI architectures.
Diffusion Models
New research introduces Generative Stochastic Optimal Transport (GenSOT), combining harmonic path-integral methods with optimal transport theory to improve guided diffusion model generation.
AI Agents
Kaggle's intensive AI agent program reveals practical insights on building production-ready systems, covering orchestration patterns, tool integration, and deployment strategies for real-world applications.
AI Architecture
From Transformers to GANs, these five foundational architectures form the backbone of AI video generation, deepfake creation, and synthetic media systems that every engineer should understand.
LLM
A comprehensive guide to fine-tuning large language models using parameter-efficient techniques like LoRA and QLoRA, from fundamentals to production deployment.
LLM Compression
Learn how to reduce a 7 billion parameter language model from ~14GB to 4.5GB using quantization, pruning, and knowledge distillation while maintaining accuracy.
LLM Agents
New research introduces a co-adaptive dual-strategy framework combining fast intuitive reasoning with slow deliberative thinking to improve LLM-based agent performance.