HuCore-68M Symbolic Topology Controller
One researcher. One RTX 4070. One custom architecture. 1.0000.
HuCore-68M is a compact symbolic topology controller trained to turn elementary word problems into structured slot/skeleton proposals.
It is not a chatbot. It is a small control model for one job:
word problem -> numeric slots -> symbolic skeleton -> checked evaluator
Example:
you have 7 apples then get 14 more and give 2 away
-> a 7 b 14 c 2 : a + b - c
This public release is weights-only and includes the evaluation test sets used in the report.
TL;DR
- 68.43M parameters
- Custom HuCore architecture: not LLaMA, not Qwen, not Gemma, not a public-model fork
- Controlled topology holdout: 240 / 240
- Local training hardware: one NVIDIA RTX 4070 Laptop GPU
- Release format: weights + test sets + reports, no implementation code
- License: CC-BY-NC-4.0
What It Does
HuCore-68M extracts a compact symbolic form from simple arithmetic word problems:
| Input pattern | Target output |
|---|---|
| add / subtract word problem | a b c : a + b - c |
| equal groups | a b : a x b |
| equal sharing | a b : a / b |
| comparison wording | a b : a + b |
The model proposes the structure. A deterministic evaluator computes the final value.
Scoreboard
Controlled topology holdout:
| Dataset | Total | Slot | Skeleton | Value |
|---|---|---|---|---|
controlled_topology_holdout_240 |
240 | 1.0000 | 1.0000 | 1.0000 |
Stress v1:
| Variant | Value Exact |
|---|---|
| punctuation_flip | 1.0000 |
| whitespace_noise | 1.0000 |
| polite_prefix | 0.8958 |
| neutral_suffix | 0.0708 |
| case_noise | 0.1583 |
| distractor_suffix_number | 0.0042 |
The stress set is included because the point is not to hide weak spots. The point is to make the boundary visible.
Repository Contents
| File | Description |
|---|---|
pytorch_model.bin |
Weights-only checkpoint |
metrics.json |
Compact metric summary |
testsets/controlled_topology_holdout_240.jsonl |
Controlled evaluation set |
testsets/stress_v1_1440.jsonl |
Stress evaluation set |
reports/benchmark_pack_v1_controlled_and_stress.md |
Evaluation report |
TRAINING_ENVIRONMENT.md |
Local training environment |
MODEL_CARD.zh-CN.md |
Chinese model card |
LICENSE.md |
CC-BY-NC-4.0 license note |
This artifact does not include source code, tokenizer files, architecture config, training scripts, or training data.
Why 68M?
This release tests a simple claim:
For controlled symbolic topology extraction, a small custom controller can be enough.
More parameters are not automatically better if the task is a narrow control problem. HuCore-68M is deliberately small so the extraction behavior can be inspected, stress-tested, and improved without hiding everything inside a large general model.
Intended Use
Use this artifact for research on:
- compact symbolic controllers;
- slot/skeleton extraction;
- boundary-first model behavior;
- deterministic evaluator pipelines;
- small-model stress testing.
Not For
HuCore-68M is not intended as:
- a general chat assistant;
- a full GSM8K solver;
- a bilingual math model;
- a commercial guardrail;
- a drop-in Transformers model.
License
All files in this public artifact are released under CC-BY-NC-4.0.
Commercial use, hosted service integration, proprietary product integration, or model distillation for commercial deployment requires separate permission from the author.