---
title: "Who cites The Power of Scale — page 3 — 1,372 citing papers"
description: "1,372 papers of the Elamur Research library cite «The Power of Scale for Parameter-Efficient Prompt Tuning», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/lester-2021-power-scale-parameter-efficient-prompt/cited-by/page/3/"
---
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# Who cites «The Power of Scale for Parameter-Efficient Prompt Tuning»

1,372 papers of our library cite it (of the 149,439 whose bibliographies we read) · 266 with a page here, the most cited first · page 3 of 3 · 201–266 · [← back to «The Power of Scale for Parameter-Efficient Prompt Tuning»](https://md.research.elamur.ai/free/en/papers/lester-2021-power-scale-parameter-efficient-prompt/)

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201. [**Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF arXiv:2309.09055**Simeng Sun, Dhawal Gupta, Mohit Iyyer*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-exploring-impact-low-rank-adaptation/)
202. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations*
203. **[Tiny Budgets, Big Gains: Parameter Placement Strategy in Parameter Super-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2025-tiny-budgets-big-gains-parameter/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jinman Zhao, Xueyan Zhang, Jiaru Li, et al.*2025 · 8 citations*
204. **[Dialect & Sentiment Identification in Nuanced Arabic Tweets Using an Ensemble of Prompt-based, Fine-tuned, and Multitask BERT-Based Models](https://md.research.elamur.ai/free/en/papers/salam-2022-dialect-sentiment-identification-nuanced-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Reem Abdel-Salam*2022 · 8 citations*
205. **[Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/szep-2026-fine-tuning-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.*2026 · 7 citations*
206. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*
207. **[Contextual Dynamic Prompting for Response Generation in Task-oriented Dialog Systems](https://md.research.elamur.ai/free/en/papers/swamy-2023-contextual-dynamic-prompting-response-generation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sandesh Swamy, Narges Tabari, Chacha Chen, et al.*2023 · 6 citations*
208. **[HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance](https://md.research.elamur.ai/free/en/papers/zhang-2026-hyperadalora-accelerating-lora-rank-allocation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Zhenjia Li, Yifan Gao, et al.*2026 · 5 citations*
209. **[RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates](https://md.research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md Kowsher, Tara Esmaeilbeig, Chun-Nam Yu, et al.*2025 · 5 citations*
210. **[Continuous Attentive Multimodal Prompt Tuning for Few-Shot Multimodal Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/jana-2024-continuous-attentive-multimodal-prompt-tuning/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Soumyadeep Jana, Animesh Dey, Ranbir Singh Sanasam*2024 · 5 citations*
211. **[A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings](https://md.research.elamur.ai/free/en/papers/gaim-2025-multi-task-benchmark-abusive-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Fitsum Gaim, Hoyun Song, Huije Lee, et al.*2025 · 3 citations*
212. [**Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layers arXiv:2503.02851**Zicong He; Boxuan Zhang;, Lu Cheng*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-shakespearean-sparks-dance-hallucination-creativity/)
213. **[rematchka at ArAIEval Shared Task: Prefix-Tuning & Prompt-tuning for Improved Detection of Propaganda and Disinformation in Arabic Social Media Content](https://md.research.elamur.ai/free/en/papers/salam-2023-rematchka-araieval-shared-task-prefix/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Reem Abdel-Salam*2023 · 3 citations*
214. **[promptolution: A Unified, Modular Framework for Prompt Optimization](https://md.research.elamur.ai/free/en/papers/zehle-2026-promptolution-unified-modular-framework-prompt/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tom Zehle, Timo Heiß, Moritz Schlager, et al.*2026 · 2 citations*
215. **[A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models](https://md.research.elamur.ai/free/en/papers/petkar-2026-graph-talks-but-who-s/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Soham Petkar, Hari Aakash K, Anirudh Vempati, et al.*2026 · 1 citation*
216. **[Concept Tokens: Learning Behavioral Embeddings Through Concept Definitions](https://md.research.elamur.ai/free/en/papers/sastre-2026-concept-tokens-learning-behavioral-embeddings/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ignacio Sastre, Aiala Rosá*2026 · 1 citation*
217. **[Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing](https://md.research.elamur.ai/free/en/papers/ye-2026-decoding-multimodal-mind-generalizable-brain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunyu Ye, Yunhao Zhang, Jingyuan Sun, et al.*2026 · 1 citation*
218. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
219. **[PersonalityDBench: A Dataset for Personality Disorders - from Modeling to Controlled Generation](https://md.research.elamur.ai/free/en/papers/ravenda-2026-personalitydbench-dataset-personality-disorders-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Federico Ravenda, Seyed Ali Bahrainian, Daniele Montagnani, et al.*2026 · 1 citation*
220. **[Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions](https://md.research.elamur.ai/free/en/papers/zhang-2026-polynomial-expansion-rank-adaptation-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Zhang, Lin Mu, Li Ni, et al.*2026 · 1 citation*
221. **[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*
222. **[PromptLab: A Collaborative Platform for Prompt Engineering and Dataset Curation](https://md.research.elamur.ai/free/en/papers/shaibani-2026-promptlab-collaborative-platform-prompt-engineering/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Maged S. Al-shaibani, Zaid Alyafeai, Dania Refai, et al.*2026 · 1 citation*
223. **[ProxyPrompt: Securing System Prompts against Prompt Extraction Attacks](https://md.research.elamur.ai/free/en/papers/zhuang-2026-proxyprompt-securing-system-prompts-against/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixiong Zhuang, Maria-Irina Nicolae, Hui-Po Wang, et al.*2026 · 1 citation*
224. **[RoZO: Geometry-Aware Zeroth-Order Fine-Tuning on Low-Rank Adapters for Black-Box Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-rozo-geometry-aware-zeroth-order/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zichen Song, Weijia Li*2026 · 1 citation*
225. [**Exploring Data and Parameter Efficient Strategies for Arabic Dialect Identifications arXiv:2509.13775**Vani Kanjirangat, Ljiljana Dolamic, Fabio Rinaldi*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kanjirangat-2025-exploring-data-parameter-efficient-strategies/)
226. [**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/)
227. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
228. **[Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganography](https://md.research.elamur.ai/free/en/papers/yan-2026-anchored-sliding-window-robust-imperceptible/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyi Yan, Shiao Meng, Yugo Murawaki*2026*
229. **[Beyond Task-Level Context: Class-Conditional Context Vectors for Implicit In-Context Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-task-level-context-class/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianxin Zhang, Yilu Hu, Teng Liu, et al.*2026*
230. **[BubbleRAG: Interactive Cognitive Offloading with Thought Bubble in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-bubblerag-interactive-cognitive-offloading-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuda Ye, Jiachuan Wang, Yongqi Zhang, et al.*2026*
231. **[CAP: Controllable Alignment Prompting for Unlearning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-cap-controllable-alignment-prompting-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaokun Wang, Jinyu Guo, Jingwen Pu, et al.*2026*
232. **[Compositional Steering of Large Language Models with Steering Tokens](https://md.research.elamur.ai/free/en/papers/radevski-2026-compositional-steering-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gorjan Radevski, Kiril Gashteovski, Giwon Hong, et al.*2026*
233. **[Context-Conditioned Masked LoRA: Dynamic Rank Routing for Compute-Efficient Parameter-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/rafiuddin-2026-context-conditioned-masked-lora-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rifat Rafiuddin, Rafae Abdullah*2026*
234. **[DPLoRA: A Dual-Pruning Framework based on ILP Optimization and Progressive Pruning for Parameter-Efficient LoRA Fine-Tuning](https://md.research.elamur.ai/free/en/papers/park-2026-dplora-dual-pruning-framework-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changjun Park, Sejong Yoon, Jaekwang Kim*2026*
235. **[Efficient Fine-Tuning Methods for Portuguese Question Answering: A Comparative Study of PEFT on BERTimbau and Exploratory Evaluation of Generative LLMs](https://md.research.elamur.ai/free/en/papers/nina-2026-efficient-fine-tuning-methods-portuguese/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Mariela M. Nina, Caio Veloso Costa, Lilian Berton, et al.*2026*
236. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
237. **[Frozen LLMs are Native Decoders for High-Norm Semantic Vectors](https://md.research.elamur.ai/free/en/papers/zeng-2026-frozen-llms-are-native-decoders/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunsheng Zeng, Yongmei Tan*2026*
238. **[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*
239. **[GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning](https://md.research.elamur.ai/free/en/papers/tian-2026-grass-gradient-based-adaptive-layer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyuan Tian, Linbo Qiao, Yu Tang, et al.*2026*
240. **[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*
241. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026*
242. **[Index-Time Prefix Injection for Multi-Tenant Retrieval: Improving Search Relevance Without Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/varshney-2026-index-time-prefix-injection-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vaibhav Varshney, Manjunatha Naik Mc*2026*
243. **[Label Words as Local Task Vectors in In-Context Learning](https://md.research.elamur.ai/free/en/papers/zheng-2026-label-words-as-local-task/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Zheng, Ming Ma, Zhongqiao Lin, et al.*2026*
244. **[LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific Tasks](https://md.research.elamur.ai/free/en/papers/lu-2026-llms-now-fine-tuning-later/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Lu, Bingsheng Yao, Shao Zhang, et al.*2026*
245. **[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*
246. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Xingle Xu, Ercong Nie, et al.*2026*
247. **[MaskedVerbalizer: Automatic Verbalizer Construction for Few-Shot Text Classification in Low-Resource Right-to-Left Languages](https://md.research.elamur.ai/free/en/papers/ullah-2026-maskedverbalizer-automatic-verbalizer-construction-few/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Faizad Ullah, Furqan Sikandar, Areeba Waqar, et al.*2026*
248. **[MaskLoRA: Low-Rank Subspace–Induced Token Masking for Efficient and Faithful Language Models](https://md.research.elamur.ai/free/en/papers/rafiuddin-2026-masklora-low-rank-subspace-induced/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rifat Rafiuddin*2026*
249. **[On the Representation Geometry of LoRA Model Merging](https://md.research.elamur.ai/free/en/papers/lu-2026-representation-geometry-lora-model-merging/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenyang Lu, Jiaru Li, Jinman Zhao, et al.*2026*
250. **[Output-Space Search: Targeting LLM Generations in a Frozen Encoder-Defined Output Space](https://md.research.elamur.ai/free/en/papers/materzok-2026-output-space-search-targeting-llm/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Tobias Materzok*2026*
251. **[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*
252. **[Reason-to-Learn (R2L): Multi-Agent Knowledge Distillation for Lightweight LLMs in Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/tu-2026-reason-learn-r2l-multi-agent/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Le-Huy Tu, Quan Nguyen, Vincent NGUYEN, et al.*2026*
253. **[RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models](https://md.research.elamur.ai/free/en/papers/moghaddam-2026-reprompt-recurrent-prompt-tuning-integrating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arya Hadizadeh Moghaddam, Drew Ross, Mohsen Nayebi Kerdabadi, et al.*2026*
254. **[Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior](https://md.research.elamur.ai/free/en/papers/nadkarni-2026-rewriting-history-recipe-interventional-analyses/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.*2026*
255. **[Safe-FedLLM: Delving into the Safety of Federated Large Language Models](https://md.research.elamur.ai/free/en/papers/tao-2026-safe-fedllm-delving-into-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingxiang Tao, Yu Tian, Wenxuan Tu, et al.*2026*
256. **[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*
257. **[Shuttle Between Symbolic Instructions and Neural Parameters of Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-shuttle-between-symbolic-instructions-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wangtao Sun, Haotian Xu, Huanxuan Liao, et al.*2026*
258. **[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*
259. **[Soft Head Selection for Injecting ICL-Derived Task Embeddings](https://md.research.elamur.ai/free/en/papers/park-2026-soft-head-selection-injecting-icl/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungwon Park, Jimyeong Kim, Changin Choi, et al.*2026*
260. **[Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-soft-orthogonal-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yitong Wang, Xue Han, WenChun Gao, et al.*2026*
261. **[Still Loading@DravidianLangTech 2026: Telugu Prompt-Style Recovery using Multilingual Transformers](https://md.research.elamur.ai/free/en/papers/sarker-2026-still-loading-dravidianlangtech-2026-telugu/) [Workshop on Speech, Vision, and Language Technologies for Dravidian Languages](https://md.research.elamur.ai/free/en/venues/dravidianlangtech/)**Samonwita Sarker, Isnat Mehrin Sami, Priyontee Mojumder, et al.*2026*
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