@misc{nasu2018nnue,
  author = {Nasu, Yu},
  title = {Efficiently Updatable Neural-Network-based Evaluation Function for Computer Shogi},
  year = {2018},
  note = {Original work on NNUE; commonly circulated in English translation},
  url = {https://github.com/asdfjkl/nnue/raw/main/nnue_en.pdf}
}

@software{stockfish2026,
  author = {{Stockfish Developers}},
  title = {Stockfish},
  year = {2026},
  url = {https://github.com/official-stockfish/Stockfish}
}

@online{stockfishnnue2026,
  author = {{Stockfish Developers}},
  title = {NNUE Documentation},
  year = {2026},
  url = {https://official-stockfish.github.io/docs/nnue-pytorch-wiki/docs/nnue.html}
}

@software{rapfi2026,
  author = {dhbloo},
  title = {Rapfi},
  year = {2026},
  url = {https://github.com/dhbloo/rapfi}
}

@inproceedings{paszke2019pytorch,
  author = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and Desmaison, Alban and K{\"o}pf, Andreas and Yang, Edward and DeVito, Zachary and Raison, Martin and Tejani, Alykhan and Chilamkurthy, Sasank and Steiner, Benoit and Fang, Lu and Bai, Junjie and Chintala, Soumith},
  title = {PyTorch: An Imperative Style, High-Performance Deep Learning Library},
  booktitle = {Advances in Neural Information Processing Systems 32},
  year = {2019},
  url = {https://papers.neurips.cc/paper_files/paper/2019/hash/bdbca288fee7f92f2bfa9f7012727740-Abstract.html}
}

@software{figrid2026,
  author = {nicotina04},
  title = {figrid-board},
  year = {2026},
  url = {https://github.com/nicotina04/figrid-board}
}

@software{bullet2026,
  author = {Wong, Jamie},
  title = {bullet: A domain-specific NNUE trainer for chess},
  year = {2026},
  note = {GPU-accelerated NNUE trainer (Rust + CUDA), targets Stockfish-style HalfKA feature layouts},
  url = {https://github.com/jw1912/bullet}
}
