SRCH:0706AE4A
AdaptToken Scaling Laws: Pretraining Loss and HHH Benchmark Accuracy from 1B to 10B Parameters
Abstract
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What is the correlation between pretraining loss reduction and downstream HHH benchmark accuracy for AdaptToken models across the 1B to 10B parameter range. 16 claims were extracted from source literature; 1 was independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 4.0/10. This report is a machine-generated literature synthesis and does not constitute original research.
Research Question
What is the correlation between pretraining loss reduction and downstream HHH benchmark accuracy for AdaptToken models across the 1B to 10B parameter range?
Verification Level
| Paper level | L2, Source-grounded claims | |
| Source-grounded claims | 16 | |
| Claim record source | parsed source sections |
Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.
Quality Tier
| Tier | Quarantine candidate | |
| Basis | Review score is below 5.0; source-level inspection is required before relying on the synthesis. |
Descriptive public triage only; this tier does not alter current publication or DOI behavior.
Quality Dimensions
| Evidence strength | LOW | |
| Citation grounding | MEDIUM | |
| Uncertainty disclosure | MEDIUM | |
| Reproducibility status | MEDIUM |
Automated triage signals derived from public fields; not human peer review or independent validation.
Correction Record
| Status | CURRENT |
| Correction count | 0 |
| Manifest contract | paper-manifest-v1.1 |
| Correction contract | correction-record-v1 |
Public corrections are additive records. Current status does not claim the synthesis is error-free.
Provenance
| Publisher | Assignee Research |
| Public provenance | L3, Claim aggregate record |
| Report artifact | Available |
| External record | Not registered |
| Claim lineage | 16 aggregate source-grounded claims |
| Review method | Automated multi-reviewer assessment |
| Quality guide | How to read scores, claims, manifests, and evidence links |
| Provenance contract | source-provenance-v1 |
| Note | Machine-generated synthesis of existing literature. Not primary research. |