State of AI
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State of AI
Summaries of Frontier AI Research Papers
10 posts · theirs
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Hierarchical Planning for Embodied Agents, Test-Driven Code Generation, and Memory-Efficient Diffusion Models
A Breakthrough in Cost, Multi-Agent Reasoning Under Uncertainty, and Hallucination Mitigation Through Nested Memory
Metis: LLM Memory Without the Cumbersome Retrieval Stack
Graph-Based Agentic AI, Adaptive Speculative Decoding, and Physics-Based Digital Twins
Gradient Bottlenecks, Token Learning Dynamics, and Agentic Self-Evolution: Understanding LLM Training and Deployment
Recursive Evidence Replay for Long-Context Reasoning, Multi-Turn Red Teaming for Code Security, and Neuron-Aware LLM Optimization
Benchmark Saturation, Self-Evolving Agents, and Trillion-Parameter Performance at 35B Scale
Diffusion Models Meet Reasoning: Learning to Schedule, Search, and Synthesize
Audio Reasoning, Hallucination Mitigation, and Efficient Inference: From Chain-of-Thought Speech Models to INT8 Diffusion Transformers
Hyperbolic Embeddings, Sparse Attention Kernels, and Diffusion-Based Retrieval: Three Breakthroughs in Scaling AI Systems
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