Mova0.5 pre-release⌕
☰
home / docs / papers / cited-by / Who cites «Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?»

Who cites «Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?»

21 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

  1. AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing — our card · 2026 · arXiv:2603.23069
  2. Benchmarking Arabic Authorship Attribution and Style Transfer with Large Language Models — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
  3. HyperStyler: Low-resource Authorship Style Transfer via Context-aware Style Navigation and Hypernetworks — 2026 · arXiv:2609.02772
  4. CAVE: Controllable Authorship Verification Explanations — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  5. Jenin at AraGenEval Shared Task: Parameter-Efficient Fine-Tuning and Layer-Wise Analysis of Arabic LLMs for Authorship Style Transfer and Classification — 2025 · Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks
  6. Steering Large Language Models with Register Analysis for Arbitrary Style Transfer — 2025 · arXiv:2505.00679
  7. Style Transfer with Multi-iteration Preference Optimization — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  8. StyleDistance: Stronger Content-Independent Style Embeddings with Synthetic Parallel Examples — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  9. DetoxLLM: A Framework for Detoxification with Explanations — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  10. Keep it Private: Unsupervised Privatization of Online Text — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  11. Large Human Language Models: A Need and the Challenges — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  12. StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements — our card · 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  13. TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  14. Combating Misinformation in the Age of LLMs: Opportunities and Challenges — 2023 · arXiv:2311.05656
  15. Learning Interpretable Style Embeddings via Prompting LLMs — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  16. ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer — 2023 · arXiv:2308.15459
  17. STEER: Unified Style Transfer with Expert Reinforcement — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  18. bao-2025-who-s-author-how-explanations
  19. cho-2025-tuning-free-personalized-alignment-trial
  20. kim-2026-interpreting-style-representations-style-eliciting
  21. liu-2024-authorship-style-transfer-policy-optimization

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/cited-by/patel-2022-low-resource-authorship-style-transfer/