---
title: "Who cites Owain Evans — page 5 — 2,381 papers of our library"
description: "2,381 papers of the Elamur Research library cite the works of Owain Evans, found in their bibliographies · page 5 of 7 · 401–500; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/owain-evans/cited-by/page/5/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/owain-evans/cited-by/page/5/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Owain Evans](https://md.research.elamur.ai/free/en/authors/owain-evans/) / [cited by](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/) / page 5

# Who cites Owain Evans

2,558 citations of their works from 2,381 papers of our library (of the 149,439 whose bibliographies we read) · 675 with a page here, the most cited first · page 5 of 7 · 401–500 · [← Owain Evans](https://md.research.elamur.ai/free/en/authors/owain-evans/)

[← prev](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/4/) **5** [6](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/6/) [7](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/7/) [next →](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/6/)

401. [**Auxiliary task demands mask the capabilities of smaller language models arXiv:2404.02418**Jennifer Hu, Michael C. Frank*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-auxiliary-task-demands-mask-capabilities/)
402. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
403. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations*
404. **[Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?](https://md.research.elamur.ai/free/en/papers/yona-2024-can-large-language-models-faithfully/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gal Yona, Roee Aharoni, Mor Geva*2024 · 40 citations*
405. [**Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models arXiv:2404.02823**Haoran Sun, Lixin Liu, Junjie Li, et al.*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-conifer-improving-complex-constrained-instruction/)
406. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
407. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
408. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
409. [**SlimPajama-DC: Understanding Data Combinations for LLM Training arXiv:2309.10818**Zhiqiang Shen, Tianhua Tao, Liqun Ma, et al.*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-slimpajama-dc-understanding-data-combinations/)
410. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
411. **[Aligning Large Language Models with Human Preferences through Representation Engineering](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-large-language-models-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Liu, Xiaohua Wang, Muling Wu, et al.*2024 · 37 citations*
412. **[LAiW: A Chinese Legal Large Language Models Benchmark](https://md.research.elamur.ai/free/en/papers/dai-2025-laiw-chinese-legal-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yongfu Dai, Duanyu Feng, Jimin Huang, et al.*2025 · 35 citations*
413. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
414. [**Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models arXiv:2411.07140**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/)
415. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
416. [**Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation arXiv:2306.05783**Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-xiezhi-ever-updating-benchmark/)
417. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
418. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/)
419. [**Airavata: Introducing Hindi Instruction-tuned LLM arXiv:2401.15006**Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/gala-2024-airavata-introducing-hindi-instruction-tuned/)
420. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
421. **[Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2025-benchmark-self-evolving-multi-agent/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.*2025 · 30 citations*
422. **[Knowledge Boundary of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/li-2025-knowledge-boundary-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moxin Li, Yong Zhao, Wenxuan Zhang, et al.*2025 · 30 citations*
423. **[CIDAR: Culturally Relevant Instruction Dataset For Arabic](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-cidar-culturally-relevant-instruction-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zaid Alyafeai, Khalid Almubarak, Ahmed Ashraf, et al.*2024 · 30 citations*
424. [**Jamba-1.5: Hybrid Transformer-Mamba Models at Scale arXiv:2408.12570**Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lenz-2024-jamba-1-5-hybrid-transformer/)
425. [**The Quantization Model of Neural Scaling arXiv:2303.13506**Eric J. Michaud, Ziming Liu, Uzay Girit, et al.*2023 · 30 citations*](https://md.research.elamur.ai/free/en/papers/michaud-2023-quantization-model-neural-scaling/)
426. **[CLAPnq: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems](https://md.research.elamur.ai/free/en/papers/rosenthal-2025-clapnq-cohesive-long-form-answers/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sara Rosenthal, Avirup Sil, Radu Florian, et al.*2025 · 29 citations*
427. **[Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guangya Wan, Yuqi Wu, Jie Chen, et al.*2025 · 29 citations*
428. [**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/)
429. **[Automatic Instruction Evolving for Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2024-automatic-instruction-evolving-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Zeng, Can Xu, Yingxiu Zhao, et al.*2024 · 28 citations*
430. **[PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2024-plug-leveraging-pivot-language-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, et al.*2024 · 28 citations*
431. **[Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance](https://md.research.elamur.ai/free/en/papers/nahum-2025-are-llms-better-than-reported/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Omer Nahum, Nitay Calderon, Orgad Keller, et al.*2025 · 27 citations*
432. **[The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM Agents](https://md.research.elamur.ai/free/en/papers/jia-2025-task-shield-enforcing-task-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiran Jia, Tong Wu, Xin Qin, et al.*2025 · 27 citations*
433. **[Towards the Law of Capacity Gap in Distilling Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-law-capacity-gap-distilling-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Zhang, Qiuchi Li, Dawei Song, et al.*2025 · 27 citations*
434. **[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*
435. [**Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models arXiv:2310.00836**Man Luo, Shrinidhi Kumbhar, Ming shen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/)
436. **[Construction Grammar Provides Unique Insight into Neural Language Models](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-construction-grammar-provides-unique-insight/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Leonie Weissweiler, Taiqi He, Naoki Otani, et al.*2023 · 26 citations*
437. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
438. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
439. **[Aligning LLMs with Individual Preferences via Interaction](https://md.research.elamur.ai/free/en/papers/wu-2025-aligning-llms-individual-preferences-interaction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shujin Wu, Yi R. Fung, Cheng Qian, et al.*2025 · 24 citations*
440. **[IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://md.research.elamur.ai/free/en/papers/baucells-2025-iberobench-benchmark-llm-evaluation-iberian/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.*2025 · 24 citations*
441. [**MiMo-Audio: Audio Language Models are Few-Shot Learners arXiv:2512.23808**Xiaomi LLM-Core Team, Dong Zhang, Gang Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)
442. [**From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning arXiv:2304.07995**Qian Liu, Fan Zhou, Zhengbao Jiang, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-zero-hero-examining-power-symbolic/)
443. [**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/)
444. **[Joint Prompt Optimization of Stacked LLMs using Variational Inference](https://md.research.elamur.ai/free/en/papers/sordoni-2023-joint-prompt-optimization-stacked-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.*2023 · 23 citations*
445. **[Do LLMs Know When to NOT Answer? Investigating Abstention Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/madhusudhan-2025-do-llms-know-when-not/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Nishanth Madhusudhan, Sathwik Tejaswi Madhusudhan, Vikas Yadav, et al.*2025 · 22 citations*
446. **[HALoGEN: Fantastic LLM Hallucinations and Where to Find Them](https://md.research.elamur.ai/free/en/papers/ravichander-2025-halogen-fantastic-llm-hallucinations-where/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abhilasha Ravichander, Shrusti Ghela, David Wadden, et al.*2025 · 22 citations*
447. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
448. [**CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction arXiv:2502.07316**Junlong Li, Daya Guo, Dejian Yang, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-codei-o-condensing-reasoning/)
449. **[Intention Analysis Makes LLMs A Good Jailbreak Defender](https://md.research.elamur.ai/free/en/papers/zhang-2025-intention-analysis-makes-llms-good/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuqi Zhang, Liang Ding, Lefei Zhang, et al.*2025 · 21 citations*
450. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
451. [**Language Models as Models of Language arXiv:2408.07144**Raphael Milliere*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/milliere-2024-language-models-models-language/)
452. [**Can Large Language Models be Good Path Planners? A Benchmark and Investigation on Spatial-temporal Reasoning arXiv:2310.03249**Mohamed Aghzal, Erion Plaku, Ziyu Yao*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/aghzal-2023-large-language-models-good-path/)
453. **[DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI](https://md.research.elamur.ai/free/en/papers/zhang-2023-dialogstudio-towards-richest-most-diverse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianguo Zhang, Kun Qian, Zhiwei Liu, et al.*2023 · 21 citations*
454. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations*
455. [**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/)
456. [**sDPO: Don't Use Your Data All at Once arXiv:2403.19270**Dahyun Kim, Yungi Kim, Wonho Song, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-sdpo-don-t-use-data/)
457. [**Timo: Towards Better Temporal Reasoning for Language Models arXiv:2406.14192**Zhaochen Su, Jun Zhang, Tong Zhu, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-timo-towards-better-temporal-reasoning/)
458. **[Ecologically Valid Explanations for Label Variation in NLI](https://md.research.elamur.ai/free/en/papers/jiang-2023-ecologically-valid-explanations-label-variation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe*2023 · 19 citations*
459. **[RECKONING: Reasoning through Dynamic Knowledge Encoding](https://md.research.elamur.ai/free/en/papers/chen-2023-reckoning-reasoning-through-dynamic-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zeming Chen, Gail Weiss, Eric Mitchell, et al.*2023 · 19 citations*
460. [**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/)
461. **[Hallucination Detection in LLMs Using Spectral Features of Attention Maps](https://md.research.elamur.ai/free/en/papers/binkowski-2025-hallucination-detection-llms-spectral-features/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jakub Binkowski, Denis Janiak, Albert Sawczyn, et al.*2025 · 18 citations*
462. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
463. **[ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events](https://md.research.elamur.ai/free/en/papers/islakoglu-2025-chronosense-exploring-temporal-understanding-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duygu Sezen Islakoglu, Jan-Christoph Kalo*2025 · 16 citations*
464. **[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*
465. **[FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation](https://md.research.elamur.ai/free/en/papers/bayat-2025-factbench-dynamic-benchmark-wild-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Farima Fatahi Bayat, Lechen Zhang, Sheza Munir, et al.*2025 · 16 citations*
466. **[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*
467. **[The "LLM World of Words" English free association norms generated by large language models](https://md.research.elamur.ai/free/en/papers/abramski-2024-llm-world-words-english-free/) [Scientific Data](https://md.research.elamur.ai/free/en/venues/scientific-data/)**Katherine Abramski, Riccardo Improta, Giulio Rossetti, et al.*2024 · 16 citations*
468. [**Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance arXiv:2507.22448**Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-falcon-h1-family-hybrid-head/)
469. **[LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch](https://md.research.elamur.ai/free/en/papers/pfister-2025-llammlein-transparent-compact-competitive-german/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jan Pfister, Julia Wunderle, Andreas Hotho*2025 · 15 citations*
470. **[Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps](https://md.research.elamur.ai/free/en/papers/tutek-2025-measuring-chain-thought-faithfulness-unlearning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.*2025 · 15 citations*
471. [**Rethinking Reflection in Pre-Training arXiv:2504.04022**Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shah-2025-rethinking-reflection-pre-training/)
472. **[Evaluating Large Language Models for Health-related Queries with Presuppositions](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*
473. [**Language Resources for Dutch Large Language Modelling arXiv:2312.12852**Bram Vanroy*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/vanroy-2023-language-resources-dutch-large-language/)
474. [**Jais 2: A Family of Arabic-Centric Open Large Language Models arXiv:2608.13580**Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2026-jais-2-family-arabic-centric/)
475. **[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*
476. **[LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs](https://md.research.elamur.ai/free/en/papers/long-2025-llms-are-biased-output-formats/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Do Xuan Long, Hai Nguyen Ngoc, Tiviatis Sim, et al.*2025 · 14 citations*
477. **[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*
478. **[Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-shallow-focus-deep-fixes-enhancing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.*2025 · 14 citations*
479. **[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*
480. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.*2026 · 13 citations*
481. **[Natural Language Processing RELIES on Linguistics](https://md.research.elamur.ai/free/en/papers/opitz-2025-natural-language-processing-relies-linguistics/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Juri Opitz, Shira Wein, Nathan Schneider*2025 · 13 citations*
482. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
483. **[LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs](https://md.research.elamur.ai/free/en/papers/chen-2025-ladm-long-context-training-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianghao Chen, Junhong Wu, Yangyifan Xu, et al.*2025 · 12 citations*
484. **[MorphMark: Flexible Adaptive Watermarking for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-morphmark-flexible-adaptive-watermarking-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqi Wang, Tianle Gu, Baoyuan Wu, et al.*2025 · 12 citations*
485. **[Prompt-Guided Internal States for Hallucination Detection of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-prompt-guided-internal-states-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fujie Zhang, Peiqi Yu, Biao Yi, et al.*2025 · 12 citations*
486. [**SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge arXiv:2509.07968**Lukas Haas, Gal Yona, Giovanni D'Antonio, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/haas-2025-simpleqa-verified-reliable-factuality-benchmark/)
487. **[SKIntern: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models](https://md.research.elamur.ai/free/en/papers/liao-2025-skintern-internalizing-symbolic-knowledge-distilling/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Huanxuan Liao, Shizhu He, Yupu Hao, et al.*2025 · 12 citations*
488. **[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*
489. **[Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text Generation](https://md.research.elamur.ai/free/en/papers/zhou-2025-balancing-diversity-risk-llm-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Zhou, Margret Keuper, Mario Fritz*2025 · 11 citations*
490. **[Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?](https://md.research.elamur.ai/free/en/papers/pan-2025-can-llm-watermarks-robustly-prevent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leyi Pan, Aiwei Liu, Shiyu Huang, et al.*2025 · 11 citations*
491. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
492. **[MDCure: A Scalable Pipeline for Multi-Document Instruction-Following](https://md.research.elamur.ai/free/en/papers/liu-2025-mdcure-scalable-pipeline-multi-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabrielle Kaili-May Liu, Bowen Shi, Avi Caciularu, et al.*2025 · 11 citations*
493. **[Multi-Attribute Steering of Language Models via Targeted Intervention](https://md.research.elamur.ai/free/en/papers/nguyen-2025-multi-attribute-steering-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.*2025 · 11 citations*
494. **[VeriFact: Enhancing Long-Form Factuality Evaluation with Refined Fact Extraction and Reference Facts](https://md.research.elamur.ai/free/en/papers/liu-2025-verifact-enhancing-long-form-factuality/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Liu, Lechen Zhang, Sheza Munir, et al.*2025 · 11 citations*
495. **[Dialogue Discourse Parsing as Generation: A Sequence-to-Sequence LLM-based Approach](https://md.research.elamur.ai/free/en/papers/li-2024-dialogue-discourse-parsing-as-generation/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Chuyuan Li, Yuwei Yin, Giuseppe Carenini*2024 · 11 citations*
496. [**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/)
497. [**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/)
498. **[Beyond the Surface: Measuring Self-Preference in LLM Judgments](https://md.research.elamur.ai/free/en/papers/chen-2025-beyond-surface-measuring-self-preference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhi-Yuan Chen, Hao Wang, Xinyu Zhang, et al.*2025 · 10 citations*
499. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
500. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*

[← prev](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/4/) **5** [6](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/6/) [7](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/7/) [next →](https://md.research.elamur.ai/free/en/authors/owain-evans/cited-by/page/6/)

- [← back to](https://md.research.elamur.ai/free/en/authors/owain-evans/) — Owain Evans