---
title: "Who cites Luo Ji — page 4 — 1,561 papers of our library"
description: "1,561 papers of the Elamur Research library cite the works of Luo Ji, found in their bibliographies · page 4 of 4 · 301–371; the most cited first."
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---
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# Who cites Luo Ji

1,561 citations of their works from 1,561 papers of our library (of the 149,439 whose bibliographies we read) · 371 with a page here, the most cited first · page 4 of 4 · 301–371 · [← Luo Ji](https://md.research.elamur.ai/free/en/authors/luo-ji/)

[← prev](https://md.research.elamur.ai/free/en/authors/luo-ji/cited-by/page/3/) [1](https://md.research.elamur.ai/free/en/authors/luo-ji/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/luo-ji/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/luo-ji/cited-by/page/3/) **4**

301. **[baellouf at AbjadMed: Efficient Fine-tuning with All-Linear LoRA for Arabic Medical QA Classification](https://md.research.elamur.ai/free/en/papers/khallouf-2026-baellouf-abjadmed-efficient-fine-tuning/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Abdallah Khallouf*2026*
302. **[Can Calibration of Positional Encodings Enhance Long Context Utilization?](https://md.research.elamur.ai/free/en/papers/zehle-2026-can-calibration-positional-encodings-enhance/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tom Zehle, Matthias Aßenmacher*2026*
303. **[Can LLMs Learn to Map the World from Local Descriptions?](https://md.research.elamur.ai/free/en/papers/xia-2026-can-llms-learn-map-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sirui Xia, Aili Chen, Xintao Wang, et al.*2026*
304. **[Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory](https://md.research.elamur.ai/free/en/papers/pothugunta-2026-carefully-considering-culture-analyzing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Krishna Pothugunta, John P. Lalor*2026*
305. **[Causal Evidence Extraction and Triangulation in Crisis Reports using Large Language Models: A ReliefWeb-based Study](https://md.research.elamur.ai/free/en/papers/zhang-2026-causal-evidence-extraction-triangulation-crisis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanjun Zhang, Mourad Oussalah*2026*
306. **[CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification](https://md.research.elamur.ai/free/en/papers/wang-2026-causaldetox-causal-head-selection-intervention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yian Wang, Yuen Chen, Agam Goyal, et al.*2026*
307. **[ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-climagent-llm-as-agents-autonomous/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Wang, Jindong Han, Wei Fan, et al.*2026*
308. **[COMPACT: Building Compliance Paralegals via Clause Graph Reasoning over Contracts](https://md.research.elamur.ai/free/en/papers/singh-2026-compact-building-compliance-paralegals-clause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ayush Singh, Dishank Aggarwal, Pranav Bhagat, et al.*2026*
309. **[Controllable Sentence Simplification in Italian: Fine-Tuning Large Language Models on Automatically Generated Resources](https://md.research.elamur.ai/free/en/papers/papucci-2026-controllable-sentence-simplification-italian-fine/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Michele Papucci, Giulia Venturi, Felice Dell'Orletta*2026*
310. **[Cultivating Forensic Reasoning for Generalizable Multimodal Manipulation Detection](https://md.research.elamur.ai/free/en/papers/zhang-2026-cultivating-forensic-reasoning-generalizable-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuchen Zhang, Yaxiong Wang, Kecheng Han, et al.*2026*
311. **[Deconstructing Instruction-Following: A New Benchmark for Granular Evaluation of Large Language Model Instruction Compliance Abilities](https://md.research.elamur.ai/free/en/papers/purpura-2026-deconstructing-instruction-following-new-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alberto Purpura, Li Wang, Sahil Badyal, et al.*2026*
312. **[Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts](https://md.research.elamur.ai/free/en/papers/zheng-2026-disentangling-reasoning-logic-resolve-explicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianda Zheng, Zijian Huang, Meng-Fen Chiang, et al.*2026*
313. **[Divergent Thinking: Escape the Homogeneity Trap in Generative Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/tao-2026-divergent-thinking-escape-homogeneity-trap/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Tao, Kaiwen Cheng, Zhiwei Nie, et al.*2026*
314. **[DNT at #SMM4H–HeaRD 2026: Leveraging BERT-based Encoders and LLMs for Medical Information Extraction](https://md.research.elamur.ai/free/en/papers/tien-2026-dnt-smm4h-heard-2026-leveraging/) [Social Media Mining for Health Research and Applications Workshop and Shared Tasks](https://md.research.elamur.ai/free/en/venues/smm4h/)**Doan Nhat Tien, Thìn Đặng Văn*2026*
315. **[Evaluating Discriminability of Vision-Language Models](https://md.research.elamur.ai/free/en/papers/muraoka-2026-evaluating-discriminability-vision-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masayasu Muraoka, Naoaki Okazaki*2026*
316. **[Evaluating Transformer Model Family Representations Through Automated Essay Scoring](https://md.research.elamur.ai/free/en/papers/ozten-2026-evaluating-transformer-model-family-representations/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Akchay Ozten, Rodrigo Wilkens*2026*
317. **[Event Detection with a Context-Aware Encoder and LoRA for Improved Performance on Long-Tailed Classes](https://md.research.elamur.ai/free/en/papers/monsur-2026-event-detection-context-aware-encoder/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abdullah Al Monsur, Nitesh Vamshi Bommisetty, Gene Louis Kim*2026*
318. **[FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models](https://md.research.elamur.ai/free/en/papers/weng-2026-finesteer-unified-framework-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Weng, Jinghuai Zhang, Kunlin Cai, et al.*2026*
319. **[From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning](https://md.research.elamur.ai/free/en/papers/wu-2026-experience-skill-multi-agent-generative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beining Wu, Fuyou Mao, Jiong Lin, et al.*2026*
320. **[From Narrow Unlearning to Emergent Misalignment in LLMs](https://md.research.elamur.ai/free/en/papers/mushtaq-2026-narrow-unlearning-emergent-misalignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna, et al.*2026*
321. **[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*
322. **[FTibSuite: A Comprehensive Resource Suite for Tibetan Vision–Language Modeling](https://md.research.elamur.ai/free/en/papers/xu-2026-ftibsuite-comprehensive-resource-suite-tibetan/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guixian Xu, Yide Liang, Zeli Su, et al.*2026*
323. **[GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-gameplayqa-benchmarking-framework-decision-dense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunzhe Wang, Runhui Xu, Kexin Zheng, et al.*2026*
324. **[How Can Synthetic Data Improve Multilingual Language Model Pretraining? A Data Quality Perspective](https://md.research.elamur.ai/free/en/papers/zhu-2026-how-can-synthetic-data-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongyao Zhu, Qian Liu, Chang Ma, et al.*2026*
325. **[HuoziIME: An On-Device LLM-Enhanced Input Method for Deep Personalization](https://md.research.elamur.ai/free/en/papers/shan-2026-huoziime-device-llm-enhanced-input/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baocai Shan, Yuzhuang Xu, Wanxiang Che*2026*
326. **[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*
327. **[Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications](https://md.research.elamur.ai/free/en/papers/lu-2026-inverting-shield-systematically-generating-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyue Lu, Xianglin Yang, Haijun Liu, et al.*2026*
328. **[KGRxn-LLM: Knowledge Graph Enhanced Large Language Models for Molecular Reaction Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2026-kgrxn-llm-knowledge-graph-enhanced/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Weichen Liu, Qiyao Xue, Yuyang Wu, et al.*2026*
329. **[L2Dir: Integrating L2-Norm and Directional Alignment for Unsupervised Contrastive Representation Learning in Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zong-2026-l2dir-integrating-l-2-norm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Zong, Rui Dai, Hongzhu Yi, et al.*2026*
330. **[Language-Aware Token Boosting: LLM Language Confusion Reduction Without Tuning](https://md.research.elamur.ai/free/en/papers/ukarapol-2026-language-aware-token-boosting-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Trapoom Ukarapol, Pakhapoom Sarapat, Nut Chukamphaeng*2026*
331. **[Large Language Models Put to the Test on Chinese Noun Compounds: Experiments on Natural Language Inference and Compound Semantics](https://md.research.elamur.ai/free/en/papers/qiu-2026-large-language-models-put-test/) [Workshop on Multiword Expressions (MWE)](https://md.research.elamur.ai/free/en/venues/mwe/)**Le Qiu, Emmanuele Chersoni, He Zhou, et al.*2026*
332. **[Large-Scale Multimodal Knowledge Graph about Classical Chinese Poetry: Fine-grained Method and Comprehensive Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-large-scale-multimodal-knowledge-graph/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuo Wang, Qing Zhu, Yang Xiao, et al.*2026*
333. **[Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection](https://md.research.elamur.ai/free/en/papers/shao-2026-leave-my-images-alone-preventing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zedian Shao, Hongbin Liu, Yuepeng Hu, et al.*2026*
334. **[Less is More: Knowledge-Aware Compression for Long Legal Judgment Prediction](https://md.research.elamur.ai/free/en/papers/lou-2026-less-is-more-knowledge-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fanghao Lou, Qiqi Wang, Guanyu Chen, et al.*2026*
335. **[MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/xiang-2026-mab-dqa-addressing-query-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Xiang, Yunshan Ma, Xiaoyu Du, et al.*2026*
336. **[Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*
337. **[Mitigating Coordinate Prediction Bias from Positional Encoding Failures](https://md.research.elamur.ai/free/en/papers/tao-2026-mitigating-coordinate-prediction-bias-positional/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjian Tao, Yiwei Wang, Yujun Cai, et al.*2026*
338. **[Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation](https://md.research.elamur.ai/free/en/papers/zhu-2026-mitigating-hallucinations-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Zhu, Junfeng Fang, Shuo Wang, et al.*2026*
339. **[Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling](https://md.research.elamur.ai/free/en/papers/liu-2026-mitigating-judgment-preference-bias-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuliang Liu, Zhipeng Xu, Zhenghao Liu, et al.*2026*
340. **[Mixture of Heterogeneous Grouped Experts for Language Modeling](https://md.research.elamur.ai/free/en/papers/ma-2026-mixture-heterogeneous-grouped-experts-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhicheng Ma, Xiang Liu, Zhaoxiang Liu, et al.*2026*
341. **[Momoka-RAG: MCTS-Organized Mapping of Knowledge Associations for Long-Document Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/tao-2026-momoka-rag-mcts-organized-mapping/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenyu Tao, Xiaofen Xing, Zeliang Li, et al.*2026*
342. **[More Than Sum of Its Parts: Deciphering Intent Shifts in Multimodal Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/sun-2026-more-than-sum-its-parts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Runze Sun, Yu Zheng, Zexuan Xiong, et al.*2026*
343. **[More Thinking, Less Talking: Internalizing Deliberative Safety into LLM Parameters](https://md.research.elamur.ai/free/en/papers/wang-2026-more-thinking-less-talking-internalizing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guan Wang, Xuehai Tang, Biyu Zhou, et al.*2026*
344. **[MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-morphobench-benchmark-difficulty-adaptive-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xukai Wang, Xuanbo Liu, Mingrui Chen, et al.*2026*
345. **[On the Robustness of Morphosyntactic Transformation with Large Language Models: The Case of Quechua Collao](https://md.research.elamur.ai/free/en/papers/pocco-2026-robustness-morphosyntactic-transformation-large-language/) [Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)](https://md.research.elamur.ai/free/en/venues/americasnlp/)**Pool Pocco, Arturo Oncevay*2026*
346. **[One LLM Does Not Simulate All Students: Ability-Aware Student Simulation via Cognitive Diagnosis Guided LLM Assignment](https://md.research.elamur.ai/free/en/papers/que-2026-one-llm-does-not-simulate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huixing Que, Qi Liu, Weibo Gao, et al.*2026*
347. **[Optimizing Efficiency in Multi-Stage Semantic Re-ranking Architectures](https://md.research.elamur.ai/free/en/papers/novais-2026-optimizing-efficiency-multi-stage-semantic/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Artur M. A. Novais, Anna P. V. L. B. Moreira, Maria C. X. de Almeida, et al.*2026*
348. **[PII Jailbreaking in LLMs via Activation Steering Reveals Personal Information Leakage](https://md.research.elamur.ai/free/en/papers/nakka-2026-pii-jailbreaking-llms-activation-steering/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Krishna Kanth Nakka, Xue Jiang, Dmitrii Usynin, et al.*2026*
349. **[Progressive Re-ranking for Multimodal Retrieval-Augmented Generation via Curriculum Learning](https://md.research.elamur.ai/free/en/papers/min-2026-progressive-re-ranking-multimodal-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhu Min, Yanchao Hao, Jian Liu, et al.*2026*
350. **[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*
351. **[Russian Generative Spelling, Punctuation and Capitalization Correction](https://md.research.elamur.ai/free/en/papers/martynov-2026-russian-generative-spelling-punctuation-capitalization/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nikita Martynov, Danil Astafurov, Ulyana Isaeva, et al.*2026*
352. **[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*
353. **[Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-law-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFan Zhang, Tao Yu, Feng Li, et al.*2026*
354. **[SceneLM: 3D-Aware Language Models for Editable 3D Scene Synthesis](https://md.research.elamur.ai/free/en/papers/yao-2026-scenelm-3d-aware-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingbo Yao, Xiaoyu Chen, Doudou Zhang, et al.*2026*
355. **[SciPedia: Unlocking the Value of Scientific Data for Pre-training](https://md.research.elamur.ai/free/en/papers/qin-2026-scipedia-unlocking-value-scientific-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiwei Qin, Zhen Huang, Tiantian Mi, et al.*2026*
356. **[SCOPE: Boosting LLM Efficiency with Scoped Position Encoding](https://md.research.elamur.ai/free/en/papers/qi-2026-scope-boosting-llm-efficiency-scoped/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingguo Qi, Hongyang Chen, Zhao Li*2026*
357. **[Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool Composition](https://md.research.elamur.ai/free/en/papers/wang-2026-simple-vgc-enhancing-visual-grounding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye Wang, Qianglong Chen, Siyuan Wang, et al.*2026*
358. **[SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic Languages](https://md.research.elamur.ai/free/en/papers/liu-2026-siniticmterror-machine-translation-dataset-error/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hannah Liu, Junghyun Min, Annie En-Shiun Lee, et al.*2026*
359. **[STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/yu-2026-stem-structure-tracing-evidence-mining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peng Yu, En Xu, Bin Chen, et al.*2026*
360. [**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/)
361. **[Structured Prompting for Arabic Essay Proficiency: A Trait-Centric Evaluation Approach](https://md.research.elamur.ai/free/en/papers/mandhari-2026-structured-prompting-arabic-essay-proficiency/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Salim Al Mandhari, Hieu Pham Dinh, Mo El-Haj, et al.*2026*
362. **[Table-R1: Region-based Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/wu-2026-table-r1-region-based-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenhe Wu, Jian Yang, Zhongjiang He, et al.*2026*
363. **[Towards Fair and Efficient De-identification: Quantifying the Efficiency and Generalizability of De-identification Approaches](https://md.research.elamur.ai/free/en/papers/zambare-2026-fair-efficient-de-identification-quantifying/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Noopur Zambare, Kiana Aghakasiri, Carissa Lin, et al.*2026*
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