---
title: "Who cites USVSN Sai Prashanth — page 2 — 506 citing papers"
description: "506 papers of the Elamur Research library cite the works of USVSN Sai Prashanth, found in their bibliographies · page 2 of 2 · 101–136; the…"
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# Who cites USVSN Sai Prashanth

521 citations of their works from 506 papers of our library (of the 149,439 whose bibliographies we read) · 136 with a page here, the most cited first · page 2 of 2 · 101–136 · [← USVSN Sai Prashanth](https://md.research.elamur.ai/free/en/authors/usvsn-sai-prashanth/)

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101. [**Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning arXiv:2301.09626**Malte Ostendorff, Georg Rehm*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/ostendorff-2023-efficient-language-model-training-through/)
102. [**Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs arXiv:2402.12030 · Transactions on Machine Learning Research, January 2025**Nicolas Boizard, Kevin El Haddad, Celine Hudelot, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2024-towards-cross-tokenizer-distillation-universal/)
103. [**Efficient Online Data Mixing For Language Model Pre-Training arXiv:2312.02406**Alon Albalak, Liangming Pan, Colin Raffel, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2023-efficient-online-data-mixing-language/)
104. [**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/)
105. [**TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer arXiv:2307.14995**Zhen Qin, Dong Li, Weigao Sun, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)
106. **[OPT-Tree: Speculative Decoding with Adaptive Draft Tree Structure](https://md.research.elamur.ai/free/en/papers/wang-2025-opt-tree-speculative-decoding-adaptive/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jikai Wang, Yi Su, Juntao Li, et al.*2025 · 32 citations*
107. [**A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean Language Models arXiv:2306.02254**Hyunwoong Ko, Kichang Yang, Minho Ryu, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/ko-2023-technical-report-polyglot-ko-open/)
108. **[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*
109. [**RWKV-7 "Goose" with Expressive Dynamic State Evolution arXiv:2503.14456**Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/peng-2025-rwkv-7-goose-expressive-dynamic/)
110. [**Knowledge Sanitization of Large Language Models arXiv:2309.11852**Yoichi Ishibashi, Hidetoshi Shimodaira*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/ishibashi-2023-knowledge-sanitization-large-language-models/)
111. **[CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/chen-2024-cofipara-coarse-fine-paradigm-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixin Chen, Hongzhan Lin, Ziyang Luo, et al.*2024 · 20 citations*
112. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
113. **[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*
114. **[Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum](https://md.research.elamur.ai/free/en/papers/pouransari-2024-dataset-decomposition-faster-llm-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.*2024 · 16 citations*
115. **[Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better](https://md.research.elamur.ai/free/en/papers/liu-2024-does-detectgpt-fully-utilize-perturbation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengchao Liu, Xiaoming Liu, Yichen Wang, et al.*2024 · 16 citations*
116. [**Linearizing Large Language Models arXiv:2405.06640**Jean Mercat, Igor Vasiljevic, Sedrick Keh, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/mercat-2024-linearizing-large-language-models/)
117. **[Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/jiang-2026-beyond-math-stories-as-testbed/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxuan Jiang, Francis Ferraro*2026 · 10 citations*
118. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
119. **[M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation](https://md.research.elamur.ai/free/en/papers/liu-2025-m2rc-eval-massively-multilingual-repository/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaheng Liu, Ken Deng, Congnan Liu, et al.*2025 · 8 citations*
120. **[Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis](https://md.research.elamur.ai/free/en/papers/boughorbel-2024-improving-language-models-trained-translated/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Sabri Boughorbel, Md Rizwan Parvez, Majd Hawasly*2024 · 8 citations*
121. [**The Arabic AI Fingerprint: Stylometric Analysis and Detection of Large Language Models Text arXiv:2505.23276**Maged S. Al-Shaibani, Moataz Ahmed*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/al-shaibani-2025-arabic-ai-fingerprint-stylometric-analysis/)
122. **[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*
123. **[Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages](https://md.research.elamur.ai/free/en/papers/niyogi-2026-paramanu-compact-competitive-monolingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026 · 5 citations*
124. **[Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-embedding-informed-adaptive-retrieval-augmented/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chengkai Huang, Yu Xia, Rui Wang, et al.*2025 · 5 citations*
125. **[HAMiSoN-Generative at ClimateActivism 2024: Stance Detection using generative large language models](https://md.research.elamur.ai/free/en/papers/hernandez-2024-hamison-generative-climateactivism-2024-stance/) [Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text](https://md.research.elamur.ai/free/en/venues/case/)**Jesus M. Fraile-Hernandez, Anselmo Peñas*2024 · 4 citations*
126. **[Are Dialects Better Prompters? A Case Study on Arabic Subjective Text Classification](https://md.research.elamur.ai/free/en/papers/moudjari-2025-are-dialects-better-prompters-case/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leila Moudjari, Farah Benamara*2025 · 3 citations*
127. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
128. **[A Survey of Large Models in Sports](https://md.research.elamur.ai/free/en/papers/xu-2026-survey-large-models-sports/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Xu, Jianzhe Ma, Chuhan Wang, et al.*2026*
129. **[Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection Methods](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-are-llm-benchmarks-already-contaminated/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.*2026*
130. **[Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling](https://md.research.elamur.ai/free/en/papers/rodkin-2026-beyond-memorization-extending-reasoning-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ivan Rodkin, Daniil Orel, Konstantin Smirnov, et al.*2026*
131. **[Exploring Cross-Client Memorization of Training Data in Large Language Models for Federated Learning](https://md.research.elamur.ai/free/en/papers/udsa-2026-exploring-cross-client-memorization-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tinnakit Udsa, Can Udomcharoenchaikit, Patomporn Payoungkhamdee, et al.*2026*
132. **[Investigating Memorization in Language Models Trained via Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/macking-2026-investigating-memorization-language-models-trained/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maarten Mäcking, Michaela Regneri*2026*
133. **[ltzGLUE: Luxembourgish General Language Understanding Evaluation](https://md.research.elamur.ai/free/en/papers/plum-2026-ltzglue-luxembourgish-general-language-understanding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alistair Plum, Felicia Körner, Anne-Marie Lutgen, et al.*2026*
134. **[PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection](https://md.research.elamur.ai/free/en/papers/liu-2026-pdr-plug-play-positional-decay/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhan Liu, Yibo Yang, Ruiying Lu, et al.*2026*
135. **[SEAD: A Surrogate-free Label-only Membership Inference Attack against Pre-trained LLMs with Semantic-Aware Density](https://md.research.elamur.ai/free/en/papers/yi-2026-sead-surrogate-free-label-only/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Biao Yi, Jiahao Li, Yiming Li, et al.*2026*
136. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*

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