---
title: "Who cites Lucia Zheng — page 4 — 1,950 papers of our library"
description: "1950 papers of the Elamur Research library cite the works of Lucia Zheng, found in their bibliographies · page 4 of 5 · 301–400; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/lucia-zheng/cited-by/page/4/"
---
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# Who cites Lucia Zheng

2,101 citations of their works from 1,950 papers of our library (of the 149,439 whose bibliographies we read) · 465 with a page here, the most cited first · page 4 of 5 · 301–400 · [← Lucia Zheng](https://md.research.elamur.ai/free/en/authors/lucia-zheng/)

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301. **[A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model](https://md.research.elamur.ai/free/en/papers/lakim-2022-holistic-assessment-carbon-footprint-noor/) [BigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language Models](https://md.research.elamur.ai/free/en/venues/bigscience/)**Imad Lakim, Ebtesam Almazrouei, Ibrahim Abualhaol, et al.*2022 · 30 citations*
302. **[Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning](https://md.research.elamur.ai/free/en/papers/weber-2023-mind-instructions-holistic-evaluation-consistency/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 29 citations*
303. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
304. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
305. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations*
306. **[Prediction of Arabic Legal Rulings using Large Language Models](https://md.research.elamur.ai/free/en/papers/ammar-2023-prediction-arabic-legal-rulings-using/) [Electronics](https://md.research.elamur.ai/free/en/venues/electronics/)**Adel Ammar, Anis Koubaa, Bilel Benjdira, et al.*2023 · 27 citations*
307. [**Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models arXiv:2306.16322**Zaid Alyafeai, Maged S. Alshaibani, Badr AlKhamissi, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-taqyim-evaluating-arabic-nlp-tasks/)
308. **[Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2024-developing-pragmatic-benchmark-assessing-korean/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yeeun Kim, Youngrok Choi, Eunkyung Choi, et al.*2024 · 24 citations*
309. **[PaniniQA: Enhancing Patient Education Through Interactive Question Answering](https://md.research.elamur.ai/free/en/papers/cai-2023-paniniqa-enhancing-patient-education-through/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pengshan Cai, Zonghai Yao, Fei Liu, et al.*2023 · 24 citations*
310. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
311. [**LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation arXiv:2401.17244**Yuan Chiang, Elvis Hsieh, Chia-Hong Chou, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2024-llamp-large-language-model-made/)
312. [**COLLIE: Systematic Construction of Constrained Text Generation Tasks arXiv:2307.08689**Shunyu Yao, Howard Chen, Austin W. Hanjie, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-collie-systematic-construction-constrained-text/)
313. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
314. **[Reasoning-to-Defend: Safety-Aware Reasoning Can Defend Large Language Models from Jailbreaking](https://md.research.elamur.ai/free/en/papers/zhu-2025-reasoning-defend-safety-aware-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junda Zhu, Lingyong Yan, Shuaiqiang Wang, et al.*2025 · 21 citations*
315. **[AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-aramus-pushing-limits-data-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaad Alghamdi, Xinyu Duan, Wei Jiang, et al.*2023 · 21 citations*
316. [**DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules**Yanchen Liu, William Held, Diyi Yang*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/)
317. [**The Vector Grounding Problem arXiv:2304.01481**Dimitri Coelho Mollo, Raphael Milliere*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/mollo-2023-vector-grounding-problem/)
318. [**Quality-Diversity through AI Feedback arXiv:2310.13032**Herbie Bradley, Andrew Dai, Hannah Teufel, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bradley-2023-quality-diversity-through-ai-feedback/)
319. **[ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability](https://md.research.elamur.ai/free/en/papers/liu-2026-reasonrank-empowering-passage-ranking-strong/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhan Liu, Xinyu Ma, Weiwei Sun, et al.*2026 · 18 citations*
320. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
321. [**Elaborative Simplification as Implicit Questions Under Discussion**Yating Wu, William Sheffield, Kyle Mahowald, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-elaborative-simplification-as-implicit-questions/)
322. [**Evaluating statistical language models as pragmatic reasoners arXiv:2305.01020**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/)
323. [**ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback arXiv:2404.00934**Zhenyu Hou, Yilin Niu, Zhengxiao Du, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/hou-2024-chatglm-rlhf-practices-aligning/)
324. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
325. [**MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models Proceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLP**Dojun Park, Jiwoo Lee, Seohyun Park, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-multiprageval-multilingual-pragmatic-evaluation-large/)
326. **[TADA : Task Agnostic Dialect Adapters for English](https://md.research.elamur.ai/free/en/papers/held-2023-tada-task-agnostic-dialect-adapters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Held, Caleb Ziems, Diyi Yang*2023 · 17 citations*
327. **[Evaluating the Consistency of LLM Evaluators](https://md.research.elamur.ai/free/en/papers/lee-2025-evaluating-consistency-llm-evaluators/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Noah Lee, Jiwoo Hong, James Thorne*2025 · 16 citations*
328. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
329. **[Translation in the Hands of Many: Centering Lay Users in Machine Translation Interactions](https://md.research.elamur.ai/free/en/papers/savoldi-2025-translation-hands-many-centering-lay/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Beatrice Savoldi, Alan Ramponi, Matteo Negri, et al.*2025 · 16 citations*
330. **[Jailbreaking LLMs with Arabic Transliteration and Arabizi](https://md.research.elamur.ai/free/en/papers/ghanim-2024-jailbreaking-llms-arabic-transliteration-arabizi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, et al.*2024 · 16 citations*
331. **[LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English](https://md.research.elamur.ai/free/en/papers/s-2024-lexsumm-lext5-benchmarking-modeling-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Santosh T.Y.S.S, Cornelius Weiss, Matthias Grabmair*2024 · 16 citations*
332. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
333. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
334. **[BALSAM: A Platform for Benchmarking Arabic Large Language Models](https://md.research.elamur.ai/free/en/papers/matham-2025-balsam-platform-benchmarking-arabic-large/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Rawan Al-Matham, Kareem Darwish, Raghad Al-Rasheed, et al.*2025 · 14 citations*
335. **[CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/leang-2025-comat-chain-mathematically-annotated-thought/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ong Jun Leang, Aryo Pradipta Gema, Shay B. Cohen*2025 · 14 citations*
336. **[Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM Reviews](https://md.research.elamur.ai/free/en/papers/shin-2025-mind-blind-spots-focus-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, et al.*2025 · 14 citations*
337. **[MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming](https://md.research.elamur.ai/free/en/papers/guo-2025-mtsa-multi-turn-safety-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Jing Li, Wenya Wang, et al.*2025 · 14 citations*
338. **[Analyzing Multilingual Competency of LLMs in Multi-Turn Instruction Following: A Case Study of Arabic](https://md.research.elamur.ai/free/en/papers/boughorbel-2023-analyzing-multilingual-competency-llms-multi/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Sabri Boughorbel, Majd Hawasly*2023 · 14 citations*
339. [**Constituency Parsing using LLMs arXiv:2310.19462**Xuefeng Bai, Jialong Wu, Yulong Chen, et al.*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-constituency-parsing-using-llms/)
340. **[Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation](https://md.research.elamur.ai/free/en/papers/kim-2024-paralinguistics-aware-speech-empowered-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, et al.*2024 · 13 citations*
341. **[Task-Agnostic Low-Rank Adapters for Unseen English Dialects](https://md.research.elamur.ai/free/en/papers/xiao-2023-task-agnostic-low-rank-adapters/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zedian Xiao, William Held, Yanchen Liu, et al.*2023 · 13 citations*
342. **[REARANK: Reasoning Re-ranking Agent via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2025-rearank-reasoning-re-ranking-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Le Zhang, Bo Wang, Xipeng Qiu, et al.*2025 · 12 citations*
343. **[Benchmarking LLaMA-3 on Arabic Language Generation Tasks](https://md.research.elamur.ai/free/en/papers/khondaker-2024-benchmarking-llama-3-arabic-language/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Md Tawkat Islam Khondaker, Numaan Naeem, Fatimah Khan, et al.*2024 · 12 citations*
344. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
345. [**The ICL Consistency Test arXiv:2312.04945**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/weber-2023-icl-consistency-test/)
346. [**E-EVAL: A Comprehensive Chinese K-12 Education Evaluation Benchmark for Large Language Models arXiv:2401.15927**Jinchang Hou, Chang Ao, Haihong Wu, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/hou-2024-e-eval-comprehensive-chinese/)
347. **[Pragmatic Competence Evaluation of Large Language Models for the Korean Language](https://md.research.elamur.ai/free/en/papers/park-2024-pragmatic-competence-evaluation-large-language/) [Pacific Asia Conference on Language, Information and Computation (PACLIC)](https://md.research.elamur.ai/free/en/venues/paclic/)**Dojun Park, Jiwoo Lee, Hyeyun Jeong, et al.*2024 · 11 citations*
348. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
349. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations*
350. [**PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation arXiv:2312.17276**Yunhe Wang, Hanting Chen, Yehui Tang, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/)
351. **[RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine Generation](https://md.research.elamur.ai/free/en/papers/li-2026-rubrichub-comprehensive-highly-discriminative-rubric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sunzhu Li, Jiale Zhao, Huimin Ren, et al.*2026 · 9 citations*
352. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
353. **[ChatBench: From Static Benchmarks to Human-AI Evaluation](https://md.research.elamur.ai/free/en/papers/chang-2025-chatbench-static-benchmarks-human-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Serina Chang, Ashton Anderson, Jake M. Hofman*2025 · 9 citations*
354. **[DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture](https://md.research.elamur.ai/free/en/papers/maji-2025-drishtikon-multimodal-multilingual-benchmark-testing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Arijit Maji, Raghvendra Kumar, Akash Ghosh, et al.*2025 · 9 citations*
355. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
356. **[TurkBench: A Benchmark for Evaluating Turkish Large Language Models](https://md.research.elamur.ai/free/en/papers/toraman-2026-turkbench-benchmark-evaluating-turkish-large/) [Workshop Natural Language Processing for Turkic Languages](https://md.research.elamur.ai/free/en/venues/sigturk/)**Cagri Toraman, Ahmet Kaan Sever, Ayşe Aysu Cengiz, et al.*2026 · 8 citations*
357. **[Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?](https://md.research.elamur.ai/free/en/papers/liu-2025-revisiting-epistemic-markers-confidence-estimation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayu Liu, Qing Zong, Weiqi Wang, et al.*2025 · 8 citations*
358. **[Bridging the Resource Gap: Exploring the Efficacy of English and Multilingual LLMs for Swedish](https://md.research.elamur.ai/free/en/papers/holmstrom-2023-bridging-resource-gap-exploring-efficacy/) [Workshop on the Role of Resources in the Age of Large Language Models](https://md.research.elamur.ai/free/en/venues/resourceful/)**Oskar Holmström, Jenny Kunz, Marco Kuhlmann*2023 · 8 citations*
359. **[Red Teaming Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/chen-2026-red-teaming-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Chen, Yang Yang, Chao Yu, et al.*2026 · 7 citations*
360. **[ICLEval: Evaluating In-Context Learning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-icleval-evaluating-context-learning-ability/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Wentong Chen, Yankai Lin, ZhenHao Zhou, et al.*2025 · 7 citations*
361. **[TLUE: A Tibetan Language Understanding Evaluation Benchmark](https://md.research.elamur.ai/free/en/papers/gao-2025-tlue-tibetan-language-understanding-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fan Gao, Cheng Huang, Yutong Liu, et al.*2025 · 7 citations*
362. [**HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew**Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/argaman-2024-hesum-novel-dataset-abstractive-text/)
363. [**Shared Imagination: LLMs Hallucinate Alike arXiv:2407.16604**Yilun Zhou, Caiming Xiong, Silvio Savarese, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-shared-imagination-llms-hallucinate-alike/)
364. **[ThatiAR: Subjectivity Detection in Arabic News Sentences](https://md.research.elamur.ai/free/en/papers/suwaileh-2024-thatiar-subjectivity-detection-arabic-news/) [Proceedings of the International AAAI Conference on Web and Social Media](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-international-aaai-conference-on-web-and-social-media/)**Reem Suwaileh, Maram Hasanain, Fatema Hubail, et al.*2024 · 7 citations*
365. **[Detecting Training Data of Large Language Models via Expectation Maximization](https://md.research.elamur.ai/free/en/papers/kim-2026-detecting-training-data-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gyuwan Kim, Yang Li, Evangelia Spiliopoulou, et al.*2026 · 5 citations*
366. [**MedAraBench: Large-Scale Arabic Medical Question Answering Dataset and Benchmark arXiv:2602.01714**Mouath Abu-Daoud, Leen Kharouf, Omar El Hajj, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/abu-daoud-2026-medarabench-large-scale-arabic-medical/)
367. **[SubLIME: Subset Selection via Rank Correlation Prediction for Data-Efficient LLM Evaluation](https://md.research.elamur.ai/free/en/papers/saranathan-2025-sublime-subset-selection-rank-correlation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gayathri Saranathan, Cong Xu, Mahammad Parwez Alam, et al.*2025 · 5 citations*
368. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
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372. **[How Quantization Shapes Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/marcuzzi-2026-how-quantization-shapes-bias-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.*2026 · 3 citations*
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374. **[Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations*
375. **[Korean Canonical Legal Benchmark: Toward Knowledge-Independent Evaluation of LLMs' Legal Reasoning Capabilities](https://md.research.elamur.ai/free/en/papers/oh-2026-korean-canonical-legal-benchmark-knowledge/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hongseok Oh, Wonseok Hwang, Kyoung-Woon On*2026 · 3 citations*
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380. **[Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization](https://md.research.elamur.ai/free/en/papers/xing-2026-are-llms-reliable-rankers-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Xing, Jerry Li, Yixuan Du, et al.*2026 · 2 citations*
381. **[Benchmarking Large Language Models for Chinese and Japanese IMEs: Phonetic-to-Character Generation and Textual Error Correction](https://md.research.elamur.ai/free/en/papers/zou-2026-benchmarking-large-language-models-chinese/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuchun Zou, Tedd Lee, Xiaodi Fan, et al.*2026 · 2 citations*
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383. **[OpenExempt: A Diagnostic Benchmark for Legal Reasoning and a Framework for Creating Custom Benchmarks on Demand](https://md.research.elamur.ai/free/en/papers/servantez-2026-openexempt-diagnostic-benchmark-legal-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sergio Servantez, Sarah B. Lawsky, Rajiv Jain, et al.*2026 · 2 citations*
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385. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
386. [**WASIL: In-the-Wild Arabic Spoken Interactions with LLMs arXiv:2605.16364**Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-wasil-wild-arabic-spoken-interactions/)
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388. **[AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agenticeval-agentic-self-evolving-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixu Wang, Xin Wang, Yang Yao, et al.*2026 · 1 citation*
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390. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
391. **[Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists](https://md.research.elamur.ai/free/en/papers/pietruszka-2026-can-models-help-us-create/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz, et al.*2026 · 1 citation*
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393. **[CuriosAI at SemEval-2026 Task 4: A Comprehensive Study of Zero-Shot versus Fine-Tuned Approaches for Narrative Similarity](https://md.research.elamur.ai/free/en/papers/shibata-2026-curiosai-semeval-2026-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Yuki Shibata, Hiroki Takushima, Fumika Beppu, et al.*2026 · 1 citation*
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396. **[From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-passive-metric-active-signal-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Zhang, Wendi Cui, Zhuohang Li, et al.*2026 · 1 citation*
397. **[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*
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399. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
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