README.md

---
license: mit
tags:
- icml2026-repro
- paper-YhEWC2HiJl
- federated-graph-learning
- graph-condensation
- text-attributed-graphs
---

# DANCE reproduction bundle

Reproduction of **DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated
Text-Attributed Graphs** (ICML 2026, OpenReview `YhEWC2HiJl`, arXiv 2601.16519).

Scope: local, single-machine (Apple M1 Pro). HF Jobs was credit-blocked (402), so the
federated 8-dataset + LLM-surrogate setting (Table 1) is out of scope; we verify the
mechanism, theory, and complexity claims, plus a single-dataset (Cora) proxy.

## Contents
- `scripts/dance_core.py` — DANCE mechanisms (node condensation, budgeted neighbor gating, sparse self-expressive topology, hard-budget projection).
- `scripts/dance_model.py` — DANCE-lite GCN + chunk gating + fusion classifier (Sec 4.3-4.4).
- `scripts/claim4_theorems.py` — Theorem 5.4 & 5.6 numerical verification.
- `scripts/claim5_complexity.py` — O(Kq) edges, time scaling, frozen-vs-LLM cost.
- `scripts/claim23_cora.py` — Claim 2 architecture invariants + Claim 3 deletion/insertion evidence tests on Cora.
- `scripts/claim1_condensation.py` — Claim 1 accuracy/token proxy on Cora.
- `scripts/make_figures.py` — figures.
- `outputs/` — result JSONs + figures.

## Rerun
```bash
uv venv --python 3.11 .venv && source .venv/bin/activate
uv pip install torch numpy scipy scikit-learn matplotlib torch_geometric
python scripts/claim4_theorems.py      # Claim 4
python scripts/claim5_complexity.py    # Claim 5
python scripts/claim23_cora.py         # Claims 2 & 3 (downloads Cora via PyG)
python scripts/claim1_condensation.py  # Claim 1
python scripts/make_figures.py
```