One workstation, 6,341 papers, 18 days: the workflow is the product
ParetoOptimal
• NEW Articles from Team or Enterprise organizations will get promoted to the main section.
Five machine raters, one definition, and answers ranging from 0 to 78
leventbulut
• On Measuring Progress Toward AGI: A Cognitive Framework
JosefAlbers
• What Is MiniMax H3 (Hailuo 3.0)? The Open-Weight Multimodal Video Model, Explained
ResterChed
• • 1int-llm precision ladder: from a wide integer oracle to compact weights
nmicic
• DeepSeek V4 Flash Is Now Official: What Changed in the 0731 Build
ResterChed
• • 1Exact E2M1 on Hopper
KissTheHabit
• Text-Only Models with mm-ctx Vision Toolkit vs. Native Vision Models
vlm-run
• Accelerating Qwen3.6 on Intel® Core™ Ultra Series 3 with DFlash
ofirzaf
• • 11mDenseOn with the mLateOn: Open Multilingual, Long-Context, and Code Retrieval Models
lightonai
• • 34Can you train a model on Simon Willison's deeply unscientific pelican benchmark?
sergiopaniego
• • 2What Do Memory Benchmarks Actually Measure? (Hint: Not Storage)
mjfk
• • 1Geometric Memory FT4 — Distill Against a Consensus, Ship a Rotation
AbstractPhil
• • 1I Built a RAG System, Then Tried to Break It
nazeerbashashaik
• • 1🎲 Apprendre à un réseau à écrire avec seulement une récompense — il a atteint 99,9 % grammatical sans apprendre une seule règle 🇫🇷
RDTvlokip
• • 5🎲 Teaching a network to write with reward only — it hit 99.9% grammatical without learning a single rule 🇫🇷
RDTvlokip
• • 124/24 Retrieval, Yet the Embeddings Changed: An MLX Q4–Q8 Sweep with CUDA Controls
TiGa-RCE
• • 2LettucePrevent - Real-Time Prevention of Factual Hallucinations in RAG
lebe1
• • 9Training a 2.7B MoE from scratch for $200, one GPU at a time
vovaRL
• • 5VisionPsy-Nano: State-of-the-Art On-Device Vision-Language Models
qvac
• • 15