---
title: "Who cites Brian Lester — page 7 — 3,131 papers of our library"
description: "3,131 papers of the Elamur Research library cite the works of Brian Lester, found in their bibliographies · page 7 of 8 · 601–700; the most cited first."
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---
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# Who cites Brian Lester

3,479 citations of their works from 3,131 papers of our library (of the 149,439 whose bibliographies we read) · 716 with a page here, the most cited first · page 7 of 8 · 601–700 · [← Brian Lester](https://md.research.elamur.ai/free/en/authors/brian-lester/)

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601. **[Decoding News Narratives: A Critical Analysis of Large Language Models in Framing Detection](https://md.research.elamur.ai/free/en/papers/pastorino-2026-decoding-news-narratives-critical-analysis/) [Workshop on Natural Language Processing for Political Sciences](https://md.research.elamur.ai/free/en/venues/politicalnlp/)**Valeria Pastorino, Jasivan Alex Sivakumar, Nafise Sadat Moosavi*2026 · 3 citations*
602. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Hao Gu, Hongming Piao, et al.*2026 · 3 citations*
603. **[Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-mitigating-catastrophic-forgetting-target-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, et al.*2026 · 3 citations*
604. **[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*
605. [**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/)
606. **[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*
607. **[Latent Agents: A Post-Training Procedure for Internalized Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/yi-2026-latent-agents-post-training-procedure/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Seon Keun Yi, Aaron Mueller, Dokyun Lee*2026 · 2 citations*
608. **[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*
609. **[Qomhrá: A Bilingual Irish and English Large Language Model](https://md.research.elamur.ai/free/en/papers/mcinerney-2026-qomhra-bilingual-irish-english-large/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Joseph McInerney, Khanh-Tung Tran, Liam Lonergan, et al.*2026 · 2 citations*
610. [**A Platform for Generating Educational Activities to Teach English as a Second Language arXiv:2504.20251**Aiala Rosa, Santiago Gongora, Juan Pablo Filevich, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/rosa-2025-platform-generating-educational-activities-teach/)
611. **[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*
612. **[Compatibility-Aware Dynamic Fine-Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-compatibility-aware-dynamic-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Junwei Sheng, Qianning Wang, et al.*2026 · 1 citation*
613. **[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*
614. **[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*
615. **[DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management](https://md.research.elamur.ai/free/en/papers/yin-2026-dmretriever-family-models-improved-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Yin, Xiangjue Dong, Chengkai Liu, et al.*2026 · 1 citation*
616. **[Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-enhancing-linguistic-competence-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Maggie Mi, Nikolaos Aletras*2026 · 1 citation*
617. **[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*
618. **[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*
619. **[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*
620. **[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*
621. **[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*
622. **[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*
623. **[Revealing Procedural Reasoning Structures in Chain-of-Thought Training via Span-Level Gradient Organization](https://md.research.elamur.ai/free/en/papers/liu-2026-revealing-procedural-reasoning-structures-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jia Liu, Jiaxin Luo, Weiwen Xu, et al.*2026 · 1 citation*
624. **[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*
625. **[SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models](https://md.research.elamur.ai/free/en/papers/nghiem-2026-smarter-data-efficient-framework-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huy Nghiem, Advik Sachdeva, Hal Daumé Iii*2026 · 1 citation*
626. **[UIT-Polar at SemEval-2026 Task 9 Detecting Multilingual, Multicultural and Multievent Online Polarization](https://md.research.elamur.ai/free/en/papers/tran-2026-uit-polar-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Hoàn Trần*2026 · 1 citation*
627. **[x1: Learning to Think Adaptively Across Languages and Cultures](https://md.research.elamur.ai/free/en/papers/ye-2026-x1-learning-think-adaptively-across/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangfan Ye, Xiaocheng Feng, Xiachong Feng, et al.*2026 · 1 citation*
628. **[Construction Grammar Evidence for How LLMs Use Context-Directed Extrapolation to Solve Tasks](https://md.research.elamur.ai/free/en/papers/madabushi-2025-construction-grammar-evidence-how-llms/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Harish Tayyar Madabushi, Claire Bonial*2025 · 1 citation*
629. [**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/)
630. **[On Reference (In-)Determinacy in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2025-reference-determinacy-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.*2025 · 1 citation*
631. **[A Layer-wise Analysis of Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2026-layer-wise-analysis-supervised-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinghua Zhao, Xueling Gong, Xinyu Chen, et al.*2026*
632. [**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/)
633. **[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*
634. **[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*
635. [**ArabicNumBench: Evaluating Arabic Number Reading in Large Language Models arXiv:2602.18776**Anas Alhumud, Abdulaziz Alhammadi, Muhammad Badruddin Khan*2026*](https://md.research.elamur.ai/free/en/papers/alhumud-2026-arabicnumbench-evaluating-arabic-number-reading/)
636. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
637. **[Beyond Static Synthetic Noise: Assessing the Robustness of Large Language Models to Natural Context Variation in the Real World](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-static-synthetic-noise-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulong Wu, Viktor Schlegel, Riza Batista-Navarro*2026*
638. **[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*
639. **[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*
640. **[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*
641. **[CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG Hallucinations](https://md.research.elamur.ai/free/en/papers/shi-2026-coda-restoring-contextual-dominance-copy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**JinWei Shi, Qizhuo Xie, Qianzi Hou, et al.*2026*
642. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*
643. **[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*
644. **[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*
645. **[Decoupled Reasoning with Implicit Fact Tokens (DRIFT): A Dual-Model Framework for Efficient Long-Context Inference](https://md.research.elamur.ai/free/en/papers/xie-2026-decoupled-reasoning-implicit-fact-tokens/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Xie, Xuhong Wang*2026*
646. **[Delayed Wh-Question Development in Children with Hearing Loss: Evidence for Morphosyntactic Vulnerability from Corpus-Based NLP and LLM Analyses](https://md.research.elamur.ai/free/en/papers/wu-2026-delayed-wh-question-development-children/) [Workshop on Linguistic Analysis for Health](https://md.research.elamur.ai/free/en/venues/healing/)**Tong Wu*2026*
647. **[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*
648. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026*
649. **[D²-RAG: Dual-Decision Retrieval-Augmented Generation via Multi-Dimensional Uncertainty and Utility-Aware Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-d-2-rag-dual-decision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinshuo Zhang, Xiaoding Zhou, Weiyu Zhang, et al.*2026*
650. **[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*
651. **[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*
652. **[From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-recognition-reasoning-benchmarking-enhancing-mllms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yandi Wang, Libin Zhan, Ziwei Huang, et al.*2026*
653. **[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*
654. **[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*
655. **[GCIG: GraphRAG-based Cross-document Instruction Generation for Boosting LLM Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-gcig-graphrag-based-cross-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoliang Xu, Huang Yuan, Junmei Wang, et al.*2026*
656. **[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*
657. **[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*
658. **[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*
659. **[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*
660. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*
661. **[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*
662. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
663. **[LLEOT: A Privacy-Enhancing Offsite Tuning Framework via Loss Landscape Elevation](https://md.research.elamur.ai/free/en/papers/zhong-2026-lleot-privacy-enhancing-offsite-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Zhong, Jinglin Liang, Tongtong Yang, et al.*2026*
664. **[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*
665. **[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*
666. **[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*
667. **[Mapping the Course for Prompt-based Structured Prediction](https://md.research.elamur.ai/free/en/papers/pauk-2026-mapping-course-prompt-based-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matt Pauk, Maria Leonor Pacheco*2026*
668. **[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*
669. **[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*
670. **[Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*
671. **[Multilingual and Cross-Lingual Citation Needed Detection on Wikipedia for Lower-Resource Languages](https://md.research.elamur.ai/free/en/papers/quaremba-2026-multilingual-cross-lingual-citation-needed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gerrit Quaremba, Amy Rechkemmer, Elizabeth Black, et al.*2026*
672. **[Multimodal Dual-Path Decoding for Medical Report Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-multimodal-dual-path-decoding-medical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghan Sun, Dong Wei, Zhihong Zhu, et al.*2026*
673. **[MzansiText and MzansiLM: An Open Corpus and Decoder-Only Language Model for South African Languages](https://md.research.elamur.ai/free/en/papers/lombard-2026-mzansitext-mzansilm-open-corpus-decoder/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anri M. Lombard, Simbarashe Mawere, Temi Aina, et al.*2026*
674. **[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*
675. **[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*
676. **[Position: Scores Without Context? Rethinking the Role of Evaluation in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/zhou-2026-position-scores-without-context-rethinking/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Jiawei Zhou*2026*
677. **[PSK@EEUCA 2026: Fine-tuning Large Language Models with Synthetic Data Augmentation for Multi-class Toxicity Detection in Gaming Chat](https://md.research.elamur.ai/free/en/papers/pulipaka-2026-psk-eeuca-2026-fine-tuning/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Srikar Kashyap Pulipaka*2026*
678. **[Ranking Human and LLM Texts Using Locality Statistics](https://md.research.elamur.ai/free/en/papers/wang-2026-ranking-human-llm-texts-locality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiyang Wang, Chen Ding, Hangfeng He*2026*
679. **[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*
680. **[ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks](https://md.research.elamur.ai/free/en/papers/lv-2026-reasmark-robust-watermark-attributing-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peizhuo Lv, Ruihua Zhou, Yunpeng Li, et al.*2026*
681. **[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*
682. **[RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context](https://md.research.elamur.ai/free/en/papers/petty-2026-relic-evaluating-complex-reasoning-recognition/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jackson Petty, Michael Y. Hu, Wentao Wang, et al.*2026*
683. **[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*
684. **[Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives](https://md.research.elamur.ai/free/en/papers/liu-2026-rethinking-data-mixture-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yajiao Liu, Congliang Chen, Junchi Yang, et al.*2026*
685. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
686. **[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*
687. **[Robust Explanations for User Trust in Enterprise NLP Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-robust-explanations-user-trust-enterprise/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guilin Zhang, Kai Zhao, Jeffrey Friedman, et al.*2026*
688. **[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*
689. **[SAMoRA: Semantic-Aware Mixture of LoRA Experts for Task-Adaptive Learning](https://md.research.elamur.ai/free/en/papers/shi-2026-samora-semantic-aware-mixture-lora/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Boyan Shi, Wei Chen, Shuyuan Zhao, et al.*2026*
690. **[Scaling Intent Understanding: A Framework for Classification with Clarification using Lightweight LLMs](https://md.research.elamur.ai/free/en/papers/nandi-2026-scaling-intent-understanding-framework-classification/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Subhadip Nandi, Tanishka Agarwal, Anshika Singh, et al.*2026*
691. **[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*
692. **[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*
693. **[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*
694. **[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*
695. **[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*
696. **[SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures](https://md.research.elamur.ai/free/en/papers/wang-2026-sop-maze-evaluating-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Wang, Zhe Tang, Zehao Jin, et al.*2026*
697. [**SteuerLLM: Local specialized large language model for German tax law analysis arXiv:2602.11081 · Scientific Reports, Volume 16, 2026**Sebastian Wind, Jeta Sopa, Laurin Schmid, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wind-2026-steuerllm-local-specialized-large-language/)
698. **[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*
699. **[SURGELLM: Rethinking Multi-Task Evaluation through Task-Aware Feature Gating with Class-Balanced Normalization](https://md.research.elamur.ai/free/en/papers/mohammad-2026-surgellm-rethinking-multi-task-evaluation/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Noor Islam S. Mohammad, Ulug Bayazit*2026*
700. **[Synthetic Instruction Generation for Low-Resource Nordic Languages: Viability and Limitations in LLM Instruction-Tuning](https://md.research.elamur.ai/free/en/papers/stenlund-2026-synthetic-instruction-generation-low-resource/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mathias Stenlund, Annika Simonsen, Lars Bungum, et al.*2026*

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