--- title: "Who cites PiSSA: Principal Singular Values — 79 citing papers" description: "79 papers of the Elamur Research library cite «PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language…" canonical: "https://research.elamur.ai/free/en/papers/meng-2024-pissa-principal-singular-values-singular/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/meng-2024-pissa-principal-singular-values-singular/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [PiSSA: Principal Singular Values and Singular…](https://md.research.elamur.ai/free/en/papers/meng-2024-pissa-principal-singular-values-singular/) / cited by # Who cites «PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models» 79 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models»](https://md.research.elamur.ai/free/en/papers/meng-2024-pissa-principal-singular-values-singular/) 1. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations* 2. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/) 3. **[BeamLoRA: Beam-Constraint Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/gu-2025-beamlora-beam-constraint-low-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naibin Gu, Zhenyu Zhang, Xiyu Liu, et al.*2025 · 6 citations* 4. **[PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation](https://md.research.elamur.ai/free/en/papers/park-2026-prisp-privacy-safe-few-shot/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junho Park, Dohoon Kim, Taesup Moon*2026 · 1 citation* 5. **[Seals-NLP at SemEval-2026 Task 9: A Comparative Study of Transformer Architectures for Polarization Detection](https://md.research.elamur.ai/free/en/papers/smith-2026-seals-nlp-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Minh Smith, Cheryl Seals*2026 · 1 citation* 6. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/) 7. **[Can Spectral-Clipping Enable Better Learning While Forgetting Less for Low-Rank Adaptation?](https://md.research.elamur.ai/free/en/papers/wi-2026-can-spectral-clipping-enable-better/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hyowon Wi, Noseong Park*2026* 8. **[G-LoRA: Global-Local Decoupled Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/xiong-2026-g-lora-global-local-decoupled/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiahao Xiong, Yihong Huang, Yihe Liu, et al.*2026* 9. **[Hebbian-Guided Bi-Directional Rank Adaptation for Parameter-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2026-hebbian-guided-bi-directional-rank/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xing Zhao, Liu Yang, Xi-Le Zhao, et al.*2026* 10. **[HiCoLoRA: Addressing Context-Prompt Misalignment via Hierarchical Collaborative LoRA for Zero-Shot DST](https://md.research.elamur.ai/free/en/papers/zhang-2026-hicolora-addressing-context-prompt-misalignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuyu Zhang, Yifan Wei, Xinru Wang, et al.*2026* 11. **[Interpretable Safety Alignment via SAE-Constructed Low-Rank Subspace Adaptation](https://md.research.elamur.ai/free/en/papers/wang-2026-interpretable-safety-alignment-sae-constructed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dianyun Wang, Qingsen Ma, Yuhu Shang, et al.*2026* 12. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026* 13. **[Localized Low-Rank Adaptation within Clustered Parameter Subspaces](https://md.research.elamur.ai/free/en/papers/xiong-2026-localized-low-rank-adaptation-within/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Xiong, Yihe Liu, Xianming Hu, et al.*2026* 14. **[RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/luo-2026-ranlora-residual-aware-nonlinear-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Luo, Yongbin Liu, Chunping Ouyang, et al.*2026* 15. **[Representation-Guided Parameter-Efficient LLM Unlearning](https://md.research.elamur.ai/free/en/papers/xiao-2026-representation-guided-parameter-efficient-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zeguan Xiao, Lang Mo, Yun Chen, et al.*2026* 16. **[SDC-LoRA: Singular-Subspace Drift Controlled LoRA to Mitigate Knowledge Forgetting](https://md.research.elamur.ai/free/en/papers/zhang-2026-sdc-lora-singular-subspace-drift/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Geyuan Zhang, Xiaofei Zhou, Shihao Liu, et al.*2026* 17. **[SLoRA: Balancing Plasticity and Forgetting in Large Language Models for Continual Learning](https://md.research.elamur.ai/free/en/papers/yang-2026-slora-balancing-plasticity-forgetting-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lina Yang, Yusheng Liao, Yanfeng Wang, et al.*2026* 18. **[TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models](https://md.research.elamur.ai/free/en/papers/wang-2026-tare-lightweight-token-aware-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Siyu Zhao*2026* 19. **[Why LoRA Fails to Forget: Regularized Low-Rank Adaptation Against Backdoors in Language Models](https://md.research.elamur.ai/free/en/papers/luong-2026-why-lora-fails-forget-regularized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang-Chau Luong, Lingwei Chen*2026* 60 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/meng-2024-pissa-principal-singular-values-singular/) — PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models