Episodes (Page 9)
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Podcast details a seven-stage LLM fine-tuning pipeline
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RENT improves LLM reasoning using unsupervised RL
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Analyzes critical points in random neural networks
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BAGEL unifies image understanding and generation
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Introduces R1-Searcher++, a framework for LLMs to improve factual question answering.
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Compares GRPO and DPO reinforcement learning algorithms for text-to-image generation.
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Presents Let Androids Dream (LAD) framework for understanding implied meanings in images.
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Introduces SmolVLM, small-scale multimodal models for efficient computing.
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Surveys Federated Learning (FL), a distributed approach for collaborative training.
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Focuses on efficient Federated Learning for autonomous mobile networks using Tiny Language Models.
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Introduces Mobile-MMLU benchmark for evaluating LLMs on mobile devices.
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Presents AI-RAN, unifying Radio Access Network and AI workloads.
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Explains fine-tuning LLMs for specialized tasks, not for new factual knowledge.
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Describes an LLM customized for explaining VHDL code in processor design.
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Introduced Adaptively Weighted Nearest Neighbors (AWNN) for matrix completion.
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Explored gradient flow dynamics in neural networks.
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Introduced WavReward for evaluating end-to-end spoken dialogue models.
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Introduced BLIP3-o, a unified multimodal model for image understanding and generation.
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Introduced CodePDE, using LLMs to generate PDE solver code.
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Investigated online learning for feedforward neural networks with sign activation.