MemoryATHENA general-NLP release

This repository contains the shared MemoryATHENA checkpoint used for six paper-aligned general-NLP tasks: SST2, MR, CR, RT, AGN, and Yahoo Answers Topics. The six tasks reuse the same frozen memory, expert readers, and router; this is one model release rather than six duplicate copies of the same weights.

Training data

The causal training stream is a general-mixed equal-token mixture of WikiText-103, Amazon Polarity review text, CC-News, and IMDB text. Training uses 20M tokens per phase, sequence length 2048, batch size 1, and seed 42. The source-memory artifact is frozen and the expert/router artifacts are included here. The training corpora are referenced by name only and are not redistributed.

Test data and protocol

The held-out evaluation tasks are SST2 (872 examples), MR (2,000), CR (2,000), RT (1,066), AGN (7,600), and Yahoo Answers Topics (60,000). The paper-aligned scorer uses domain-conditional PMI with next-token log-probability sums over label synonyms; labels are used only for final accuracy calculation. Raw test examples and labels are not included.

Results (accuracy percent)

Condition SST2 MR CR RT AGN Yahoo
Historical Vanilla Mistral reference 81.08 75.60 74.00 74.67 73.24 55.03
Engram-only (forced E path) 84.17 81.00 82.40 82.36 72.93 57.51
Three-model router, default tau=0 88.07 84.70 84.10 83.86 76.64 45.91
Three-model router, Yahoo tau=1.0 post-hoc sweep 88.07 84.70 84.10 83.86 76.64 57.43

The Vanilla reference uses a historical scorer and is not a fully protocol-matched headline comparison. The Yahoo tau=1.0 value is a post-hoc test-set threshold sweep and must not be read as an independently validation-selected default; the default tau=0 row is retained.

Files and links

No ARTIFACTS.md, raw datasets, raw test examples, labels, prediction lists, optimizer states, credentials, or internal filesystem paths are part of this release.

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