---
title: "Who cites Pratyush Maini — 214 papers of our library"
description: "214 papers of the Elamur Research library cite the works of Pratyush Maini, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/pratyush-maini/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/pratyush-maini/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Pratyush Maini](https://md.research.elamur.ai/free/en/authors/pratyush-maini/) / cited by

# Who cites Pratyush Maini

215 citations of their works from 214 papers of our library (of the 149,439 whose bibliographies we read) · 58 with a page here, the most cited first · [← Pratyush Maini](https://md.research.elamur.ai/free/en/authors/pratyush-maini/)

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. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 347 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
3. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
4. [**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/)
5. [**The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning arXiv:2403.03218**Nathaniel Li, Alexander Pan, Anjali Gopal, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-wmdp-benchmark-measuring-reducing-malicious/)
6. [**Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning arXiv:2404.05868**Ruiqi Zhang, Licong Lin, Yu Bai, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-negative-preference-optimization-catastrophic-collapse/)
7. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
8. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
9. **[Machine Unlearning of Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/yao-2024-machine-unlearning-pre-trained-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Yao, Eli Chien, Minxin Du, et al.*2024 · 86 citations*
10. **[Towards Safer Large Language Models through Machine Unlearning](https://md.research.elamur.ai/free/en/papers/liu-2024-safer-large-language-models-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.*2024 · 72 citations*
11. **[C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness](https://md.research.elamur.ai/free/en/papers/kang-2024-c3ot-generating-shorter-chain-thought/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Kang, Xianghui Sun, Liangyu Chen, et al.*2024 · 66 citations*
12. **[Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset](https://md.research.elamur.ai/free/en/papers/su-2025-nemotron-cc-transforming-common-crawl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Su, Kezhi Kong, Ying Lin, et al.*2025 · 65 citations*
13. **[Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://md.research.elamur.ai/free/en/papers/cheng-2024-instruction-pre-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.*2024 · 59 citations*
14. **[SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning](https://md.research.elamur.ai/free/en/papers/jia-2024-soul-unlocking-power-second-order/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jinghan Jia, Yihua Zhang, Yimeng Zhang, et al.*2024 · 46 citations*
15. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
16. **[Towards Effective and Efficient Continual Pre-training of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-effective-efficient-continual-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.*2025 · 29 citations*
17. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
18. **[Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench](https://md.research.elamur.ai/free/en/papers/liu-2025-protecting-privacy-multimodal-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.*2025 · 24 citations*
19. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
20. **[Soft Prompting for Unlearning in Large Language Models](https://md.research.elamur.ai/free/en/papers/bhaila-2025-soft-prompting-unlearning-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Karuna Bhaila, Minh-Hao Van, Xintao Wu*2025 · 16 citations*
21. **[Alignment at Pre-training! Towards Native Alignment for Arabic LLMs](https://md.research.elamur.ai/free/en/papers/liang-2024-alignment-pre-training-towards-native/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.*2024 · 14 citations*
22. **[Learning to Refuse: Towards Mitigating Privacy Risks in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-learning-refuse-mitigating-privacy-risks/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhenhua Liu, Tong Zhu, Chuanyuan Tan, et al.*2025 · 13 citations*
23. [**Language Models can Self-Lengthen to Generate Long Texts arXiv:2410.23933**Shanghaoran Quan, Tianyi Tang, Bowen Yu, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/quan-2024-language-models-self-lengthen-generate/)
24. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.*2025 · 12 citations*
25. [**RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models arXiv:2406.01983**Bichen Wang, Yuzhe Zi, Yixin Sun, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rkld-reverse-kl-divergence-based/)
26. **[Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models](https://md.research.elamur.ai/free/en/papers/mekala-2025-alternate-preference-optimization-unlearning-factual/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Anmol Mekala, Vineeth Dorna, Shreya Dubey, et al.*2025 · 10 citations*
27. **[FAME: Fictional Actors for Multilingual Erasure](https://md.research.elamur.ai/free/en/papers/savelli-2026-fame-fictional-actors-multilingual-erasure/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.*2026 · 7 citations*
28. **[ArabicSense: A Benchmark for Evaluating Commonsense Reasoning in Arabic with Large Language Models](https://md.research.elamur.ai/free/en/papers/lamsiyah-2025-arabicsense-benchmark-evaluating-commonsense-reasoning/) [Workshop on Arabic Corpus Linguistics](https://md.research.elamur.ai/free/en/venues/wacl/)**Salima Lamsiyah, Kamyar Zeinalipour, Samir El amrany, et al.*2025 · 7 citations*
29. **[Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization](https://md.research.elamur.ai/free/en/papers/zhang-2025-get-confused-cautiously-textual-sequence/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2025 · 7 citations*
30. **[SVELA at EVALITA 2026: Overview of the Selective Verification of Erasure from LLM Answers Task](https://md.research.elamur.ai/free/en/papers/savelli-2026-svela-evalita-2026-overview-selective/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.*2026 · 6 citations*
31. **[Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks](https://md.research.elamur.ai/free/en/papers/pan-2025-analyzing-dialectical-biases-llms-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Eileen Pan, Anna Seo Gyeong Choi, Maartje Ter Hoeve, et al.*2025 · 6 citations*
32. [**Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic arXiv:2412.04277**Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-arabic-stable-lm-adapting-stable/)
33. **[Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation](https://md.research.elamur.ai/free/en/papers/burns-2026-aleph-alpha-germanweb-improving-german/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.*2026 · 4 citations*
34. **[BLUR: A Bi-Level Optimization Approach for LLM Unlearning](https://md.research.elamur.ai/free/en/papers/reisizadeh-2026-blur-bi-level-optimization-approach/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, et al.*2026 · 4 citations*
35. **[OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-offside-benchmarking-unlearning-misinformation-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zheng, Zirui Pang, Ling Li, et al.*2026 · 4 citations*
36. **[Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/lei-2026-writing-rl-advancing-long-form/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanyu Lei, Chenliang Li, Yuning Wu, et al.*2026 · 4 citations*
37. **[Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning](https://md.research.elamur.ai/free/en/papers/zhai-2026-maximizing-local-entropy-where-it/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naixin Zhai, Pengyang Shao, Binbin Zheng, et al.*2026 · 2 citations*
38. **[Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem](https://md.research.elamur.ai/free/en/papers/xiao-2026-modeling-llm-unlearning-as-asymmetric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeguan Xiao, Siqing Li, Yong Wang, et al.*2026 · 2 citations*
39. **[Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-erasing-without-remembering-implicit-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huazheng Wang, Yongcheng Jing, Haifeng Sun, et al.*2026 · 1 citation*
40. **[Ita-Lib at SVELA: Detecting the Forgotten –- Representation-Based Approach for Verifying Machine Unlearning](https://md.research.elamur.ai/free/en/papers/yassine-2026-ita-lib-svela-detecting-forgotten/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Ali Yassine, Hadi Ibrahim, Luca Cagliero*2026 · 1 citation*
41. **[MALTO at SVELA: A Specific-Attention-Head Approach for Membership Inference Attacks in LLMs Unlearning Evaluation](https://md.research.elamur.ai/free/en/papers/munis-2026-malto-svela-specific-attention-head/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Evren A. Munis, Mattia Sabato, Erfan Bayat, et al.*2026 · 1 citation*
42. **[Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic Perspectives](https://md.research.elamur.ai/free/en/papers/xu-2026-modeling-annotator-disagreement-demographic-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinuo Xu, Veronica Derricks, Allison Earl, et al.*2026 · 1 citation*
43. **[Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models](https://md.research.elamur.ai/free/en/papers/shukla-2026-calibration-vs-decision-making-revisiting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Divyaksh Shukla, Ashutosh Modi*2026*
44. **[CAP: Controllable Alignment Prompting for Unlearning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-cap-controllable-alignment-prompting-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaokun Wang, Jinyu Guo, Jingwen Pu, et al.*2026*
45. **[From Domains to Instances: Dual-Granularity Data Synthesis for LLM Unlearning](https://md.research.elamur.ai/free/en/papers/xu-2026-domains-instances-dual-granularity-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoyu Xu, Minxin Du, Zitong LI, et al.*2026*
46. **[Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations](https://md.research.elamur.ai/free/en/papers/luo-2026-graph-assisted-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haitong Luo, Fali Wang, Weiyao Zhang, et al.*2026*
47. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
48. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
49. **[LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points](https://md.research.elamur.ai/free/en/papers/zhang-2026-linkqa-synthesizing-diverse-qa-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuemiao Zhang, Can Ren, Chengying Tu, et al.*2026*
50. **[LOKA: Conflict-Aware LLM Knowledge Update with Adaptive Knowledge Memory](https://md.research.elamur.ai/free/en/papers/zhang-2026-loka-conflict-aware-llm-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binchi Zhang, Zhengzhang Chen, Zaiyi Zheng, et al.*2026*
51. **[LOTUS: Evolving Multimodal Unlearning via Hyperbolic Entailment and Lorentz Transport](https://md.research.elamur.ai/free/en/papers/wang-2026-lotus-evolving-multimodal-unlearning-hyperbolic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zekun Wang, Jingjie Zeng, Yingxu Li, et al.*2026*
52. **[priyam_saha17 at SVELA: A Feature-Centric Pipeline for Verifying Selective Forgetting in Large Language Models](https://md.research.elamur.ai/free/en/papers/saha-2026-priyam-saha17-svela-feature-centric/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Priyam Saha*2026*
53. **[Representation-Guided Parameter-Efficient LLM Unlearning](https://md.research.elamur.ai/free/en/papers/xiao-2026-representation-guided-parameter-efficient-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zeguan Xiao, Lang Mo, Yun Chen, et al.*2026*
54. **[Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space](https://md.research.elamur.ai/free/en/papers/zhang-2026-rotation-control-unlearning-quantifying-controlling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiang Zhang, Kun Wei, Xu Yang, et al.*2026*
55. **[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*
56. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Tong, Weidong Zhang, Jiaang Li, et al.*2026*
57. **[Selective Span-Level Unlearning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yoon-2026-selective-span-level-unlearning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaewon Yoon, Dongjun Kim, Hyun-Je Song*2026*
58. **[Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note Scale](https://md.research.elamur.ai/free/en/papers/liu-2026-systematic-evaluation-quality-synthetic-clinical/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Jinghui Liu, Sarvesh Soni, Anthony Nguyen*2026*

156 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/pratyush-maini/) — Pratyush Maini