---
title: "Who cites Charith Peris — 272 papers of our library"
description: "272 papers of the Elamur Research library cite the works of Charith Peris, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/charith-peris/cited-by/"
---
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# Who cites Charith Peris

278 citations of their works from 272 papers of our library (of the 149,439 whose bibliographies we read) · 60 with a page here, the most cited first · [← Charith Peris](https://md.research.elamur.ai/free/en/authors/charith-peris/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
3. [**A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly arXiv:2312.02003**Yifan Yao, Jinhao Duan, Kaidi Xu, et al.*2023 · 1,186 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-survey-large-language-model-llm/)
4. **[MTEB: Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,032 citations*
5. **[Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 814 citations*
6. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
7. [**BloombergGPT: A Large Language Model for Finance arXiv:2303.17564**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 618 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/)
8. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
9. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
10. **[The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 262 citations*
11. **[In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 243 citations*
12. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models arXiv:2405.17428**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 222 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
13. [**IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages arXiv:2305.16307**Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.*2023 · 200 citations*](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/)
14. **[ELEPHANT: Measuring and understanding social sycophancy in LLMs](https://md.research.elamur.ai/free/en/papers/cheng-2025-elephant-measuring-understanding-social-sycophancy/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Myra Cheng, Sunny Yu, Cinoo Lee, et al.*2025 · 188 citations*
15. **[Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages](https://md.research.elamur.ai/free/en/papers/doddapaneni-2023-leaving-no-indic-language-behind/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh, et al.*2023 · 174 citations*
16. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas arXiv:2406.20094**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
17. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
18. [**SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects arXiv:2309.07445**David Ifeoluwa Adelani, Hannah Liu, Xiaoyu Shen, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2023-sib-200-simple-inclusive-big/)
19. [**Knowledge Unlearning for Mitigating Privacy Risks in Language Models arXiv:2210.01504**Joel Jang, Dongkeun Yoon, Sohee Yang, et al.*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/jang-2022-knowledge-unlearning-mitigating-privacy-risks/)
20. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
21. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
22. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
23. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
24. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
25. [**Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM arXiv:2303.01911**Rachel Bawden, François Yvon*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2023-investigating-translation-performance-large-multilingual/)
26. **[Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation](https://md.research.elamur.ai/free/en/papers/majewska-2023-cross-lingual-dialogue-dataset-creation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Olga Majewska, Evgeniia Razumovskaia, Edoardo M. Ponti, et al.*2023 · 51 citations*
27. **[Benchmarking Distributional Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/meister-2025-benchmarking-distributional-alignment-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto*2025 · 35 citations*
28. **[Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement](https://md.research.elamur.ai/free/en/papers/sun-2025-persona-db-efficient-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenkai Sun, Ke Yang, Revanth Gangi Reddy, et al.*2025 · 29 citations*
29. **[LangBridge: Multilingual Reasoning Without Multilingual Supervision](https://md.research.elamur.ai/free/en/papers/yoon-2024-langbridge-multilingual-reasoning-without-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.*2024 · 29 citations*
30. **[Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions](https://md.research.elamur.ai/free/en/papers/suh-2025-language-model-fine-tuning-scaled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Erfan Jahanparast, Suhong Moon, et al.*2025 · 28 citations*
31. **[Middle-Layer Representation Alignment for Cross-Lingual Transfer in Fine-Tuned LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-middle-layer-representation-alignment-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danni Liu, Jan Niehues*2025 · 23 citations*
32. **[Can Language Models Reason about Individualistic Human Values and Preferences?](https://md.research.elamur.ai/free/en/papers/jiang-2025-can-language-models-reason-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liwei Jiang, Taylor Sorensen, Sydney Levine, et al.*2025 · 21 citations*
33. **[Multi 3 WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems](https://md.research.elamur.ai/free/en/papers/hu-2023-multi-3-woz-multilingual-multi/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Songbo Hu, Han Zhou, Mete Hergul, et al.*2023 · 17 citations*
34. **[PL-MTEB: Polish Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/poswiata-2026-pl-mteb-polish-massive-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rafał Poświata, Sławomir Dadas, Michał Wiktor Perełkiewicz*2026 · 16 citations*
35. **[URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base](https://md.research.elamur.ai/free/en/papers/khan-2025-uriel-enhancing-linguistic-inclusion-usability/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Aditya Khan, Mason Shipton, David Anugraha, et al.*2025 · 15 citations*
36. **[Value Profiles for Encoding Human Variation](https://md.research.elamur.ai/free/en/papers/sorensen-2025-value-profiles-encoding-human-variation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.*2025 · 15 citations*
37. **[Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks](https://md.research.elamur.ai/free/en/papers/bhatia-2025-swan-arabicmteb-dialect-aware-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gagan Bhatia, El Moatez Billah Nagoudi, Abdellah El Mekki, et al.*2025 · 13 citations*
38. **[A Rigorous Evaluation of LLM Data Generation Strategies for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/anikina-2025-rigorous-evaluation-llm-data-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tatiana Anikina, Jan Cegin, Jakub Simko, et al.*2025 · 11 citations*
39. [**Survey of Abstract Meaning Representation: Then, Now, Future**Behrooz Mansouri*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mansouri-2025-survey-abstract-meaning-representation-then/)
40. [**Just read twice: closing the recall gap for recurrent language models arXiv:2407.05483**Simran Arora; Aman Timalsina; Aaryan Singhal; Benjamin Spector; Sabri Eyuboglu; Xinyi Zhao; Ashish Rao; Atri Rudra;, Christopher Re*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-just-read-twice-closing-recall/)
41. **[New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*
42. **[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*
43. **[Hala Technical Report Building Arabic-Centric Instruction & Translation Models at Scale](https://md.research.elamur.ai/free/en/papers/hammoud-2026-hala-technical-report-building-arabic/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Hasan Abed Al Kader Hammoud, Mohamad Bilal Zbib, Bernard Ghanem*2026 · 5 citations*
44. **[AfriMTEB and AfriE5: Benchmarking and Adapting Text Embedding Models for African Languages](https://md.research.elamur.ai/free/en/papers/uemura-2026-afrimteb-afrie5-benchmarking-adapting-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kosei Uemura, Miaoran Zhang, David Ifeoluwa Adelani*2026 · 4 citations*
45. **[MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch](https://md.research.elamur.ai/free/en/papers/banar-2026-mteb-nl-e5-nl-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nikolay Banar, Ehsan Lotfi, Jens Van Nooten, et al.*2026 · 4 citations*
46. **[Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects](https://md.research.elamur.ai/free/en/papers/blaschke-2026-standard-dialect-transfer-trends-differ/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Verena Blaschke, Miriam Winkler, Barbara Plank*2026 · 4 citations*
47. **[Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification](https://md.research.elamur.ai/free/en/papers/pecher-2026-better-as-generators-than-classifiers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Branislav Pecher, Jan Cegin, Robert Belanec, et al.*2026 · 1 citation*
48. **[SynthLLM: An LLM-based Scalable Synthetic Data Generation Pipeline for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/panahi-2026-synthllm-llm-based-scalable-synthetic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Solmaz Panahi, Vasudevan Nedumpozhimana, John Kelleher*2026 · 1 citation*
49. **[Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/oh-2026-template-assisted-contrastive-learning-task/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minsik Oh, Jiwei Li, Guoyin Wang*2026 · 1 citation*
50. **[Investigating Zero-shot Cross-lingual Language Understanding for Arabic](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-investigating-zero-shot-cross-lingual/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Zaid Alyafeai, Moataz Ahmed*2023 · 1 citation*
51. **[Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences](https://md.research.elamur.ai/free/en/papers/ramirez-2026-controlling-what-you-share-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guillem Ramírez, Alexandra Birch, Ivan Titov*2026*
52. **[E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral-benchmarks/) [IEEE Access](https://md.research.elamur.ai/free/en/venues/ieee-access/)**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*
53. [**E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding arXiv:2609.33530**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral/)
54. **[Fill-in-the-Blanks: Automatic Generation and Evaluation of Language Models' Pseudonyms for English and Swedish Texts](https://md.research.elamur.ai/free/en/papers/szawerna-2026-fill-blanks-automatic-generation-evaluation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maria Irena Szawerna, Jacob Lee Suchardt*2026*
55. **[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*
56. [**NADI 2026: The Second Multidialectal Arabic Speech Processing Shared Task arXiv:2609.27086**Peter Sullivan, Bashar Talafha, Ahmed Ashraf, et al.*2026*](https://md.research.elamur.ai/free/en/papers/sullivan-2026-nadi-2026-second-multidialectal-arabic/)
57. **[Nanda Family: Open-Weights Generative Large Language Models for Hindi](https://md.research.elamur.ai/free/en/papers/singh-2026-nanda-family-open-weights-generative/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aaryamonvikram Singh, Debopriyo Banerjee, Dhruv Sahnan, et al.*2026*
58. **[Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus](https://md.research.elamur.ai/free/en/papers/oberkircher-2026-saar-voice-multi-speaker-saarbrucken/) [Workshop on Dialects in NLP –- A Resource Perspective](https://md.research.elamur.ai/free/en/venues/dialres/)**Lena Sophie Oberkircher, Jesujoba Alabi, Dietrich Klakow, et al.*2026*
59. **[Thinking Twice Makes Large Language Models Safer and More Helpful](https://md.research.elamur.ai/free/en/papers/mou-2026-thinking-twice-makes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2026*
60. **[UNSC-Bench: Evaluating LLM Diplomatic Role-Playing Through UN Security Council Vote Prediction](https://md.research.elamur.ai/free/en/papers/nangia-2026-unsc-bench-evaluating-llm-diplomatic/) [Workshop on Multilingual Multicultural Evaluation](https://md.research.elamur.ai/free/en/venues/mme/)**Ayush Nangia, Aman Gokrani, Ruggero Marino Lazzaroni*2026*

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