Add XLSR-SLS scores for DECRO

submissions/xlsr-sls.yaml

@@ -0,0 +1,45 @@
+schema_version: 4
+system:
+  name: XLSR-SLS
+  slug: xlsr-sls
+  description: wav2vec 2.0 (XLS-R 300M) self-supervised front-end with the SLS (Sensitive Layer Selection) classifier for
+    audio deepfake detection. SLS gates and fuses the hidden states of all XLS-R transformer layers — each layer contributing
+    distinct discriminative cues — via a per-layer sigmoid attention, sums the weighted multi-layer feature, then a BN + max-pool
+    + two-layer MLP head emits a 2-way log-softmax. Official QiShanZhang/SLSforASVspoof-2021-DF checkpoint (model_15, dev-EER
+    1.45%), trained on ASVspoof2019 LA, FP32, deterministic first-64600-sample window (no random crop).
+  code: https://github.com/QiShanZhang/SLSforASVspoof-2021-DF
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/XLSR-SLS
+  params_millions: 340.79
+  paper:
+    arxiv_id: 10.1145/3664647.3681345
+    url: https://doi.org/10.1145/3664647.3681345
+    bibtex: "@inproceedings{zhang2024audio,\n  title={Audio Deepfake Detection with Self-Supervised XLS-R and SLS Classifier},\n\
+      \  author={Zhang, Qishan and Wen, Shuangbing and Hu, Tao},\n  booktitle={Proceedings of the 32nd ACM International Conference\
+      \ on Multimedia},\n  pages={6765--6773},\n  year={2024},\n  doi={10.1145/3664647.3681345}\n}\n"
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/DECRO
+  revision: bb6df2524eadaab6aa6a2366a41a2a5fe1e4104d
+  split: test
+scores:
+  eer_percent: 12.10082159188074
+  n_trials: 37314
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/XLSR-SLS/resolve/9abaf08c439da101296387b79acdae74107d24ae/.eval_results/SpeechAntiSpoofingBenchmarks/DECRO/scores.txt
+  scores_sha256: e0ebab9f11083901a6e2c75d5c3a78fa90f659c4218ef125b1ed01cdde7ef73b
+  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: 'XLS-R 300M (wav2vec 2.0) front-end + SLS (Sensitive Layer Selection) classifier, from QiShanZhang/SLSforASVspoof-2021-DF
+  (ACM MM 2024). Architecture is built from the base xlsr2_300m.pt model config (shared with the W2V2-AASIST submission),
+  then every weight is overwritten by the fine-tuned checkpoint. SLS pools every transformer layer''s hidden state, gates
+  each by a learned sigmoid attention, and fuses them before a small MLP head. Deterministic first-64600-sample window (no
+  random crop); the head''s fc1 expects this fixed length. score = log-softmax output for class 1 (bona fide); higher = more
+  bona fide (source main.py: batch_score = batch_out[:, 1]).'