📦 Model Compression - all666666all · Scour

Trainable Smooth-Rotation Transforms with Learned Channel Scales for LLM Quantization

⚙️AutoML Academic

Less-relevant results

iblameandrew/open-deepthink: Grok-heavy at the price of API cost. You choose the model. An unlimited army to think about your problem.

🤝Multi-Agent Systems Code

github.com··r/LocalLLaMA

Heterophily-Aware Adaptive Knowledge Distillation for Hypergraph Neural Networks

⚙️AutoML Academic

MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning

💬Prompt Engineering Academic

Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin

⚙️AutoML Academic

ScaleSweep: Accurate NVFP4 Post-Training Quantization of LLMs via Block Scale Initialization

⚙️AutoML Academic

Dew Drop - June 8, 2026 (#4685)

💬Prompt Engineering

alvinashcraft.com·

LLM-Based User Personas for Recommendations at Scale

🔍Vector Databases Academic

PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning

🔍Vector Databases Academic

Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm

⚙️AutoML Academic

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models

⚙️AutoML Academic

Beyond Dark Knowledge: Mixup-Based Distillation for Reliable Predictions

🔍Vector Databases Academic

TENP: Trapezoidal Expert Neuron Pruning For Mixture-of-Experts

💬Prompt Engineering Academic

FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models

💬Prompt Engineering Academic

LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models

⚙️AutoML Academic

Sigma-Branch: Hierarchical Single-Path Network Reconstruction for Dynamic Inference with Reduced Active Parameters

⚙️AutoML Academic

Value-and-Structure Alignment for Routing-Consistent Quantization of Mixture-of-Experts Models

⚙️AutoML Academic

Unsupervised Continual Clustering via Forward-Backward Knowledge Distillation

⚙️AutoML Academic

Compress-Distill: Reasoning Trace Compression for Efficient Knowledge Distillation

💬Prompt Engineering Academic

Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry

💬Prompt Engineering Academic

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