AI: post transformers

Por: mcgrof
The transformer architecture revolutionized the world of Neural Networks. It was a springboard for what we know today as modern artificial intelligence. This podcast focuses on modern state of the art research paper reviews starting from the transformer and on.
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Latest episodes of the podcast AI: post transformers

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Doubly Stochastic Attention for Transformers 10/11/2025
Random Walk Methods for Graph Learning and Networks 10/11/2025
AlphaEvolve: Mathematical Discovery at Scale 10/11/2025
AdaFlow: Variance-Adaptive Flow-Based Imitation Learning 10/11/2025
Samsung: zFLoRA: Zero-Latency Fused Low-Rank Adapters 04/11/2025
SuperBPE: Space Travel for Language Models 04/11/2025
Google: Supervised Reinforcement Learning for Step-wise Reasoning in LLMs 04/11/2025
MorphKV: Constant-Sized KV Caches for LLM Inference 04/11/2025
HALoS: Hierarchical Asynchronous LLM Training over Slow Networks 04/11/2025
Anchored Diffusion Language Model: Superior Generation and Reasoning 04/11/2025
Gumbel-Softmax for Differentiable Categorical Reparameterization and Selective Networks 04/11/2025
PolicySmith: Automated Systems Heuristic Generation via LLMs 04/11/2025
RetNet: Retentive Networks: Transformer Successor for Large Language Models 02/11/2025
Kimi Linear: Efficient Expressive Attention Architecture 02/11/2025
ALiBi: Attention with Linear Biases Enables Length Extrapolation 01/11/2025
Quest: Query-Aware Sparsity for Efficient LLM Inference 31/10/2025
Flash-LLM: Efficient LLM Inference with Unstructured Sparsity on Tensor Cores 31/10/2025
ELASTIC: Linear Attention for Sequential Interest Compression 31/10/2025
Anthropic: Introspective Awareness in LLMs 31/10/2025
Small Versus Large Models for Requirements Classification 31/10/2025
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