Add AASIST3 scores for DECRO

submissions/aasist3.yaml

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+schema_version: 4
+system:
+  name: AASIST3
+  slug: aasist3
+  description: 'KAN-enhanced AASIST speech deepfake detector with a wav2vec 2.0 (XLS-R-53) self-supervised front-end. SSL
+    features are projected to 128-d through a Kolmogorov-Arnold (KAN) bridge, processed by a RawNet2-style residual encoder
+    and spectro-temporal graph-attention layers, and classified by a four-branch inference head with a KAN output layer. ASVspoof
+    2024 Challenge system; the published lab260/AASIST3 checkpoint (note: these weights differ from the paper results). FP32,
+    preemphasis (0.97), deterministic first-64600-sample window (no random crop). score = output logit for class 1 (bona fide).'
+  code: https://github.com/mtuciru/AASIST3
+  checkpoint: https://huggingface.co/lab260/AASIST3
+  params_millions: 321.7495
+  paper:
+    arxiv_id: '2408.17352'
+    url: https://arxiv.org/abs/2408.17352
+    bibtex: "@inproceedings{borodin24_asvspoof,\n  title={AASIST3: KAN-enhanced AASIST speech deepfake detection using SSL\
+      \ features and additional regularization for the ASVspoof 2024 Challenge},\n  author={Borodin, Kirill and Kudryavtsev,\
+      \ Vasiliy and Korzh, Dmitrii and Efimenko, Alexey and Mkrtchian, Grach and Gorodnichev, Mikhail and Rogov, Oleg Y.},\n\
+      \  booktitle={The Automatic Speaker Verification Spoofing Countermeasures Workshop (ASVspoof 2024)},\n  pages={48--55},\n\
+      \  year={2024},\n  doi={10.21437/ASVspoof.2024-8}\n}\n"
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/DECRO
+  revision: bb6df2524eadaab6aa6a2366a41a2a5fe1e4104d
+  split: test
+scores:
+  eer_percent: 23.58451987062716
+  n_trials: 37314
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/lab260/AASIST3/resolve/176b079c1efbba8d7746032609eab688e9ca2ec3/.eval_results/SpeechAntiSpoofingBenchmarks/DECRO/scores.txt
+  scores_sha256: 1a705b0e8bf61a315bb852de43fecebce1428bb808590b4d5d7fe797684eedf5
+  bench_version: speech-spoof-bench==0.3.4
+reproduction:
+  reproduced_by: SpeechAntiSpoofingBenchmarks
+  reproduced_at: '2026-06-10'
+  reproduced_bench_version: speech-spoof-bench==0.3.4
+  match: scoring
+submitter:
+  hf_username: korallll
+  contact: k.n.borodin@mtuci.ru
+submitted_at: '2026-06-10'
+notes: AASIST3 (KAN-enhanced AASIST + wav2vec 2.0 XLS-R-53 SSL front-end) from mtuciru/AASIST3, weights from lab260/AASIST3
+  (model.safetensors, self-contained incl. the SSL encoder). Loaded via PyTorchModelHubMixin.from_pretrained; the XLS-R architecture
+  is built from the wav2vec2-large-xlsr-53 config then every weight is overwritten by the checkpoint. Preemphasis (0.97) applied
+  to the full waveform before a deterministic first-64600-sample window, matching the source datasets/generic.py eval pipeline.
+  score = logit for class 1 (bona fide); higher = more bona fide (source label map bonafide=1, validation uses outputs[:,
+  1]).