LoGo preserves the reported scaling behavior of full-attention Transformers from 200M through 3.3B parameters, matching or improving the baseline on the listed language-modeling and commonsense metrics.

LoGo preserves the reported scaling behavior of full-attention Transformers from 200M through 3.3B parameters, matching or improving the baseline on the listed language-modeling and commonsense metrics. · CiteArk

Measurement results

0/3 assessed

0 supported0 disputed or conflicting3 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Metric and conditions	Reported	Latest observation	Evidence judgment
comparison: full-attention Transformer · model_variant: LoGo · reported_scope: single run · parameter_count: 3.3B · training_corpus: in-house corpus similar to Seed-OSS	1.996 loss	—	Not assessed
dataset: WikiText · model_variant: LoGo · reported_scope: single run · parameter_count: 3.3B	14.785 perplexity	—	Not assessed
model_variant: LoGo · reported_scope: single reported evaluation · parameter_count: 3.3B	58.26 percentage_points	—	Not assessed

LoGo preserves the reported scaling behavior of full-attention Transformers from 200M through 3.3B parameters, matching or improving the baseline on the listed language-modeling and commonsense metrics.

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results