val_bpb
1.2580
Architecture
Transformer
Optimizer
—
Artifact Size
15,829,207 bytes
Training Techniques
Test-Time Training
score-first TTT
parameters: {"adapter":"ACSA","reset_between_documents":true}
Other
other
Activation-Space Compressed-Sensing Adapters (ACSA) that adapt hidden activations with a sparse code instead of LoRA weight deltas.
parameters: {"targets":["postblock"],"optional_targets":["prehead"]}
Compression
zlib
level: null
Sequence Length
sequence_length
train_length: 1024
eval_length: 1024
Quantization
int8
bits: 8
scope: model artifact
Novel Contributions
- Activation-Space Compressed-Sensing Adapters (ACSA) as an alternative to LoRA-based evaluation-time adaptation
- Sparse activation-space adaptation using a structured sensing map with sign flips, permutation, and FWHT
- Preservation of score-before-update evaluation protocol with adapter state reset between documents
- Non-record SP1024 submission demonstrating improvement over the quantized no-ACSA roundtrip while staying under the 16 MB artifact cap