From 37ba0f83e3652a215680fd8515af9c14fc02e21c Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Mon, 4 May 2026 23:07:10 -0500 Subject: =?UTF-8?q?Rename=20method=20GRAFT=20=E2=86=92=20KAFT=20in=20user-?= =?UTF-8?q?facing=20README?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Internal code identifiers (GraphGrAPETrainer class, graft_* file prefixes, 'GRAFT' JSON dataset keys) are kept for backwards compatibility with results/ and earlier figure caches; a note at the top of the README points this out so reviewers don't get confused. --- README.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index db3413b..c0979c6 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,8 @@ -# GRAFT (KAFT): Topology-Factorized Jacobian-Aligned Feedback for Deep GNNs +# KAFT: Topology-Factorized Jacobian-Aligned Feedback for Deep GNNs + +> Internal class names (`GraphGrAPETrainer`, file paths starting with +> `graft_*` / dataset keys `'GRAFT'`) are the original code identifier. +> The method is referred to as **KAFT** in the paper. Code release accompanying the NeurIPS 2026 submission. @@ -20,7 +24,7 @@ computed in O(1) parallel depth on GPUs. ``` src/ core method - trainers.py BPTrainer, GraphGrAPETrainer (KAFT), DFA/DFA-GNN, alignment + trainers.py BPTrainer, GraphGrAPETrainer (= KAFT), DFA/DFA-GNN, alignment data.py PyG dataset loaders, normalized  / row-Â, sparse-mm helpers experiments/ one runner per reported result block (see `## Reproducing`) figures/ figure generators + the four rendered PDFs in the paper -- cgit v1.2.3