docs/related_work.md

Closest existing code-scaling work

Scaling Laws for Code: Every Programming Language Matters

ACL Findings paper: https://aclanthology.org/2026.findings-acl.487/

Earlier arXiv version: https://arxiv.org/abs/2512.13472 (v1, 2025-12-15).

This is directly aligned with the original Code-ATLAS idea: it fits language-specific code scaling laws, measures a bilingual synergy matrix, and fits a proportion-dependent multilingual allocation law. It reports more than 1,000 runs and studies seven languages: Python, Java, JavaScript, TypeScript, C#, Go, and Rust.

Important differences that preserve a substantial Code-ATLAS contribution:

• It covers seven high-resource languages rather than roughly 20--24 languages spanning COBOL, Fortran, Zig, OCaml, Haskell, Julia, and other resource bands.
• It does not use ATLAS's directed time-to-same-loss Bilingual Transfer Score or repetition-aware effective-data saturation law.
• Its bilingual experiment compares 64B target + 64B auxiliary tokens against a 128B repeated-target baseline; Code-ATLAS will retain ATLAS's 50/50 time-to-same-loss formulation at a fixed reference horizon.
• Its reported 900B-token parallel code corpus is Python-pivoted and its public paper does not identify the corpus sources, per-language availability, licenses, revisions, deduplication procedure, or a downloadable corpus and training pipeline. It therefore cannot be used as Code-ATLAS training data. Code-ATLAS makes provenance, licenses, dedup clusters, split IDs, and measured-versus-estimated transfer cells public.
• The arXiv v1 limitations explicitly list low-resource and domain-specific languages as unstudied. The ACL final replaced that substantive limitations text with a summary, so claims about the limitation must be version-labelled.
• The published equations, experimental contrasts, and aggregate results are useful hypotheses and baselines, but the reported transfer coefficients and mixture should not be imported as data: several equations, table values, and prose claims are internally inconsistent, and the underlying corpus is not auditable.

Accordingly, Code-ATLAS should position itself as a broader, provenance-first, ATLAS-faithful replication and extension, not as the first multilingual code scaling-law paper.