s4 (structured state spaces),s4,structured state spaces,llm architecture
Efficient SSM using special parameterization.
311 technical terms and definitions
Efficient SSM using special parameterization.
Structured State Space model uses diagonal approximations for efficient training.
Simplified diagonal state space model improves training stability and efficiency.
Safety classifiers predict whether content violates policy guidelines.
Safety fine-tuning adjusts model parameters to reduce harmful outputs.
Systems preventing harmful outputs.
Safety stock is buffer inventory maintained to protect against demand variability and supply disruptions ensuring production continuity.
Safety training teaches models to decline harmful requests and follow guidelines.
Safety = preventing harmful, illegal, or sensitive outputs. Use policies, classifiers, rule-based filters, and human review for high-risk use cases.
Self-Attention Graph Pooling selects important nodes based on learned attention scores enabling differentiable coarsening for graph classification.
Use attention for pooling.
Highlight which input tokens most influence the output.
Universal segmentation model.
Sandwich rule trains largest and smallest subnetworks alternately plus random architectures for better supernet training.
Mix standard and efficient layers.
SAP provides ERP solutions for semiconductor manufacturing including production planning quality management and supply chain integration.
Seasonal ARIMA extends ARIMA by incorporating seasonal differencing and seasonal AR/MA terms for periodic patterns.
SavedModel is TensorFlow's universal serialization format including computation graph and metadata.
Scalable oversight develops methods for humans to supervise superhuman AI systems.
Scale AI provides enterprise data labeling. Nucleus for data curation.
Theory that simply making models larger leads to better performance.
Relationships between model size data size compute and performance.
Scan chain stitching connects scan cells into shift register chains.
Scan chains convert sequential elements into shift registers enabling serial access to internal states for controllability and observability.
串联 flip-flops for testing internal logic.
Ultrasonic imaging for defects.
Planned downtime for PM.
Schema validation verifies generated structured data matches specifications.
Continuous-filter equivariant network for molecules.
SchNet uses continuous-filter convolutions on interatomic distances with rotationally invariant features for quantum chemistry predictions.
Science-based targets align emissions reductions with climate science to limit global warming.
ML for scientific computing.
Entailment from science questions.
Scope 1 emissions are direct greenhouse gas emissions from fab operations including process gases combustion and fugitive emissions.
Scope 2 emissions are indirect emissions from purchased electricity steam heating and cooling consumed by fab operations.
Scope 3 emissions include indirect supply chain emissions from materials transportation business travel and product use.
Score distillation sampling uses diffusion model gradients to optimize 3D representations.
Train by matching score functions.
Train by matching data scores.
Unified framework connecting scores and diffusion.
Generate by learning score function.
Generate CAMs without gradients.
Evaluate quality of docking poses.
Scribble conditioning interprets rough sketches as spatial guidance for generation.
Condition on rough sketches.
Scrubber systems remove hazardous gases from process tool exhaust through chemical reaction or adsorption before atmospheric release.
Stable Diffusion upscaling.
Soft Defect Localization uses stimulation and imaging techniques to reveal intermittent or parametric failures.
SE(3) Transformer processes 3D point clouds and molecular structures with equivariance to rotation and translation through spherical harmonics.
Transformers with 3D symmetries.