Remove wst-graph-q81 submission (maintainer 2026-11-10: keep only WST-Graph-Q82)

submissions/wst-graph-q81.yaml

@@ -1,60 +0,0 @@
-schema_version: 4
-system:
-  name: WST-Graph-Q81
-  slug: wst-graph-q81
-  description: 'WST-Graph (Ng et al., 2026), configuration Q81: a fixed, parameter-free Kymatio wavelet
-    scattering transform (J=8, Q=(8, 1), first + second order, oversampling 1) with log-modulation path
-    normalisation, arranged as a modulation-carrier grid (OrderGrid), length-aware attentive pooling to
-    64 relative-time bins (ALAP), a channel adapter + depthwise-separable latent blocks and an AASIST
-    graph back-end (GraphAASIST). Trained on ASVspoof 2019 LA train (focal loss, 12 epochs), training
-    seed 9 (the paper names no headline seed; seed 9 is the model card''s example). Authors'' traced TorchScript
-    program, run as released. Input as the model card: 16 kHz, no normalisation, first 64000 samples (4
-    s), right zero-pad, input_length = retained sample count. score = logit[bona fide] - logit[spoof]
-    (logits[:,0]-logits[:,1]). FP32 (TF32 off).'
-  code: https://huggingface.co/kwokho1/wst-graph/tree/080000c1685451c7759f43d2ae7d0f08477cfdf8
-  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/WST-Graph-Q81/blob/40a9a88d14bec5f0355fecb45bdc9562bda8db33/wst_graph_q81_seed9_batch32_cuda.ts
-  params_millions: 0.119867
-  paper:
-    arxiv_id: '2609.29372'
-    url: https://arxiv.org/abs/2609.29372
-    bibtex: "@article{ng2026wstgraph,\n  title   = {WST-Graph: Topology-Preserving Wavelet Scattering\
-      \ Front-End for Speech Deepfake Detection},\n  author  = {Ng, Kwok-Ho and Song, Tingting and Feng,\
-      \ Bingwen and Xia, Zhihua},\n  journal = {arXiv preprint arXiv:2609.29372},\n  year    = {2026}\n\
-      }\n"
-dataset:
-  id: SpeechAntiSpoofingBenchmarks/DECRO
-  revision: e54c29df5b81bac75e5cc294d1ab0d4db72a5c71
-  split: test
-scores:
-  eer_percent: 23.788988438231904
-  n_trials: 37314
-  n_skipped: 0
-artifact:
-  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/WST-Graph-Q81/resolve/8fded073ed6df46c2c946a0d3a7181d358d1cd79/.eval_results/SpeechAntiSpoofingBenchmarks/DECRO/scores.txt
-  scores_sha256: 50b495958b357e5e4e1a9ff84e9484dc223fa6b5410ef727051175098e64e6e0
-  bench_version: speech-spoof-bench==0.4.1
-reproduction:
-  reproduced_by: SpeechAntiSpoofingBenchmarks
-  reproduced_at: '2026-11-10'
-  reproduced_bench_version: speech-spoof-bench==0.4.1
-  match: inference
-submitter:
-  hf_username: korallll
-  contact: k.n.borodin@mtuci.ru
-submitted_at: '2026-11-10'
-notes: 'WST-Graph-Q81 = HF kwokho1/wst-graph @ 080000c1685451c7759f43d2ae7d0f08477cfdf8, q81-seed9/wst_graph_q81_seed9_batch32_cuda.ts
-  (sha256 6cd912bc7a2ecf0fd869ddaa441f50341b5cd07ce764d430f22889cf8dbf22d5; MIT, re-hosted). No Python
-  source is released (GitHub saki-ciallo/WST-Graph promised); the traced TorchScript program is the authors''
-  whole waveform-to-logits path. It was reviewed before running (code/ dir and model.code/graph of every
-  submodule): only aten::/prim:: ops, only the model''s own classes, pickles hold only tensors; the wrapper
-  re-asserts the aten/prim-only op set on load. The _cuda program has cuda:0 baked in (CUDA only). Despite
-  the "batch32" name it is batch-dynamic (verified B=1..48); B=1 takes a different cuFFT/GEMM path (|d
-  score| up to 0.013 vs B>=2, which agree to ~4e-5), so the wrapper pads a lone clip with one zero clip
-  (input_length 1) and drops it. Seed choice: the paper (Table 6) reports single-seed results without
-  naming the seed and Tables 1-5 report three-seed averages, so seed 9 (model card example) is used for
-  both Q81 and Q82; not chosen on Arena data. Wrapper = model-card quick start exactly (same-batch |d|
-  = 0). Empty clips (the card raises) get a zero waveform with input_length 1. Trained on ASVspoof 2019
-  LA train (dev for selection); the Arena 19LA set is eval -> no trained_on entries. Self-reported EER%:
-  19LA 3.07 / ITW 46.07 / 21LA 13.92 / 21DF 21.00 / ASV5 33.84 / DFADD 15.23 / LibriSeVoc 38.14 / SONAR
-  35.78 (Table 6, single seed, Speech DF Arena protocol). ASVspoof2019_LA 2000-clip eval subset with this
-  wrapper: 3.595%. J-SPAW_LA scored with this wrapper (EER 44.458%).'