Topic · 4 recaps

Small / On-device Models

Compact language and vision models designed to run on phones, laptops, and edge hardware — usually under a few billion parameters, often with aggressive distillation or quantization.

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Topic · 4 recaps

Small / On-device Models

Compact language and vision models designed to run on phones, laptops, and edge hardware — usually under a few billion parameters, often with aggressive distillation or quantization.

Posts Questions

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Revisiting Complete Reasoning Traces for Post-Training

LLM Training · Sep 7

Rethinking On-Policy Distillation of Large Language Models II: One Training Example

Inference Optimization · Sep 3

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

Inference Optimization · Aug 27

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

Multimodal · Jul 20 · 7:25

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