Add DF Arena 1B submission (eer=17.3410%, scoring-verified)

submissions/df-arena-1b.yaml

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+schema_version: 4
+system:
+  name: DF Arena 1B
+  slug: df-arena-1b
+  description: RAPTOR universal anti-spoofing model. A wav2vec 2.0 XLS-R 1B self-supervised front-end
+    whose per-layer hidden states are combined by learnable attention pooling (a layer-wise sigmoid gate
+    over an attention-pooled summary), then passed through a 4-block Conformer head with a class token
+    to a 2-way classifier. FP32, deterministic first-64600-sample (~4.04 s @ 16 kHz) window, tile-repeat
+    if shorter (no random crop, no resampling). score = softmax(logits)[bonafide]; higher = more bona
+    fide. Official Speech-Arena-2025/DF_Arena_1B_V_1 checkpoint.
+  code: https://huggingface.co/Speech-Arena-2025/DF_Arena_1B_V_1
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/DF_Arena_1B_V_1
+  params_millions: 1147.8453
+  paper:
+    arxiv_id: '2603.06164'
+    url: https://arxiv.org/abs/2603.06164
+    bibtex: "@misc{kulkarni2026compactsslbackbonesmatter,\n  title={Do Compact SSL Backbones Matter for\
+      \ Audio Deepfake Detection? A Controlled Study with RAPTOR},\n  author={Ajinkya Kulkarni and Sandipana\
+      \ Dowerah and Atharva Kulkarni and Tanel Alumäe and Mathew Magimai Doss},\n  year={2026},\n  eprint={2603.06164},\n\
+      \  archivePrefix={arXiv},\n  primaryClass={cs.SD},\n  url={https://arxiv.org/abs/2603.06164}\n}\n"
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/ASVspoof5
+  revision: 9937de5e630b137bb31e9f5901209b2705ddef63
+  split: test
+scores:
+  eer_percent: 17.34102696456098
+  n_trials: 680774
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/DF_Arena_1B_V_1/resolve/f5723c9737ae58d39013a8a6cc1955254b4a9f82/.eval_results/SpeechAntiSpoofingBenchmarks/ASVspoof5/scores.txt
+  scores_sha256: 2526209142dcfd72d0d3bbf2b45c06edd9bc05c928a98e91d9162173da5ff89e
+  bench_version: speech-spoof-bench==0.4.1
+submitter:
+  hf_username: korallll
+  contact: kborodin.research@gmail.com
+submitted_at: '2026-06-25'
+notes: DF Arena 1B (RAPTOR family), XLS-R 1B (wav2vec 2.0) front-end + attention layer pooling + 4-block
+  Conformer back-end. Architecture is built from the facebook/wav2vec2-xls-r-1b config, then every weight
+  is overwritten by the fine-tuned checkpoint (pytorch_model.bin). Trained on traditional + singing +
+  environmental deepfake corpora (ASVspoof 2019/2024, Codecfake, LibriSeVoc, DFADD, CTRSVDD, SpoofCeleb,
+  MLAAD, EnvSDD). The vendored forward feeds a real (B,T) batch to the SSL model (source hard-coded batch-1
+  via unsqueeze(0)); numerically identical per item in eval() (BatchNorm uses running stats). Deterministic
+  first-64600-sample window. score = output softmax prob for class 1 (bona fide); higher = more bona fide.
+reproduction:
+  reproduced_by: SpeechAntiSpoofingBenchmarks
+  reproduced_at: '2026-06-25'
+  reproduced_bench_version: speech-spoof-bench==0.4.1
+  match: scoring