ate, ate, advanced test & probe
Automated Test Equipment executes test programs coordinating instruments timing and data collection for high-throughput semiconductor testing.
9,967 technical terms and definitions
Automated Test Equipment executes test programs coordinating instruments timing and data collection for high-throughput semiconductor testing.
Retrieval-augmented model for knowledge-intensive tasks.
Robot that operates in normal atmosphere or N2 environment.
3D atomic-scale composition analysis.
Local atomic neighborhood features.
Measure roughness at atomic scale.
Automatic Test Pattern Generation algorithmically creates test vectors to detect specific faults or maximize fault coverage in digital circuits.
Attention mechanism as retrieval.
Add positional bias efficiently.
Study how far attention reaches.
Trace attention patterns through network.
Attention flow tracks information propagation through attention mechanisms across layers.
Attention mechanisms in time series weight historical values adaptively for improved forecasting accuracy.
Different functions of attention heads.
Scale attention by head dimension.
Binary mask indicating which tokens to attend to vs ignore (for padding).
Attention-based graph pooling learns soft cluster assignments through self-attention over node features.
Aggregate attention across layers.
Aggregate attention across layers for interpretability.
Attention rollout computes effective attention by multiplying attention weights across transformer layers.
Keep first tokens for stable attention.
Transfer attention maps from teacher.
See what model focuses on.
Visualize what model attends to.
Attention visualization displays learned attention weights revealing which inputs influence outputs.
Inspect attention weights to see what the model focuses on.
Attention-based explanations visualize which user history items or features influenced specific recommendations.
Use attention to weight modalities.
Attention computes Query-Key-Value: softmax(QK^T/sqrt(d))V. Each token attends to all others, enabling long-range dependencies.
AttentionNAS discovers efficient attention mechanisms and architectures jointly through neural architecture search.
Use attention to guide mixing.
AttentiveNAS uses attention mechanisms to predict architecture performance from training statistics without full training.
Partially transmit and phase-shift light.
Attribute agreement analysis assesses consistency of categorical judgments between appraisers.
Edit specific image attributes.
Charts for discrete data.
Whether attributed sources are correct.
Provide sources for claims.
Attribute predictions to components.
Attribution links generated claims to supporting evidence in sources.
Track which retrieved sources support each part of the generated answer.
Discrete audio tokens from neural codecs enable language model approaches to audio generation.
Create music speech or sound effects using AI.
Audio generation creates speech (TTS) or music. WaveNet, Bark, MusicGen. Multimodal applications.
Fill in missing or corrupted portions of audio.
Audio-driven animation systems generate facial expressions and head movements from speech signals.
Match audio and video.
Learn associations between audio and vision.
Audio-visual fusion combines acoustic and visual features through concatenation attention or multiplicative interactions.
Learn from audio and video together.