🚨This week’s top AI/ML research papers: - Mixture-of-Transformers - BitNet a4.8 - LoRA vs Full Fine-tuning: An Illusion of Equivalence - Mixtures of In-Context Learners - Emergence of Hidden Capabilities - DimensionX - The Surprising Effectiveness of Test-Time Training for Abstract Reasoning - OpenCoder: The Open Cookbook for Top-Tier Code LLMs - ReCapture - Needle Threading - M3DocRAG - Controlling Language and Diffusion Models by Transporting Activations - Why Do We Need Weight Decay in Modern Deep Learning? - "Give Me BF16 or Give Me Death"? Trade-Offs in LLM Quantization - Adaptive Caching for Faster Video Generation with Diffusion Transformers - Constant Acceleration Flow - Randomized Autoregressive Visual Generation - Physics in Next-token Prediction - In-Context LoRA for Diffusion Transformers - Balancing Pipeline Parallelism with Vocabulary Parallelism - EoRA: Eigenspace Low-Rank Approximation - Self-Consistency Preference Optimization - How Transformers Solve Propositional Logic Problems: A Mechanistic Analysis - LASER: Attention with Exponential Transformation - Photon: Federated LLM Pre-Training - Attacking Vision-Language Computer Agents via Pop-ups - Hunyuan-Large - Context Parallelism for Scalable Million-Token Inference - Stealing User Prompts from Mixture of Experts - Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond - Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge overview for each + authors' explanations read this in thread mode for the best experience