---
title: "Who cites Vaibhav Srivastav — 214 papers of our library"
description: "214 papers of the Elamur Research library cite the works of Vaibhav Srivastav, found in their bibliographies; the most cited first."
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---
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# Who cites Vaibhav Srivastav

217 citations of their works from 214 papers of our library (of the 149,439 whose bibliographies we read) · 51 with a page here, the most cited first · [← Vaibhav Srivastav](https://md.research.elamur.ai/free/en/authors/vaibhav-srivastav/)

1. [**Understanding R1-Zero-Like Training: A Critical Perspective arXiv:2503.20783**Zichen Liu, Changyu Chen, Wenjun Li, et al.*2025 · 286 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-understanding-r1-zero-like-training/)
2. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
3. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
4. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
5. [**Small Language Models are the Future of Agentic AI arXiv:2506.02153**Peter Belcak, Greg Heinrich, Shizhe Diao, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/belcak-2025-small-language-models-future-agentic/)
6. [**Dream 7B: Diffusion Large Language Models arXiv:2508.15487**Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)
7. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/)
8. [**SmolVLM: Redefining small and efficient multimodal models arXiv:2504.05299**Andres Marafioti, Orr Zohar, Miquel Farre, et al.*2025 · 56 citations*](https://md.research.elamur.ai/free/en/papers/marafioti-2025-smolvlm-redefining-small-efficient-multimodal/)
9. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
10. [**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/)
11. [**Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining arXiv:2504.07912**Rosie Zhao, Alexandru Meterez, Sham Kakade, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-echo-chamber-rl-post-training/)
12. **[NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions](https://md.research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weizhe Yuan, Jane Yu, Song Jiang, et al.*2025 · 26 citations*
13. [**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/)
14. [**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/)
15. [**MegaMath: Pushing the Limits of Open Math Corpora arXiv:2504.02807**Fan Zhou, Zengzhi Wang, Nikhil Ranjan, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-megamath-pushing-limits-open-math/)
16. [**Rewriting Pre-Training Data Boosts LLM Performance in Math and Code arXiv:2505.02881**Kazuki Fujii, Yukito Tajima, Sakae Mizuki, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2025-rewriting-pre-training-data-boosts/)
17. **[From Language to Cognition: How LLMs Outgrow the Human Language Network](https://md.research.elamur.ai/free/en/papers/alkhamissi-2025-language-cognition-how-llms-outgrow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Badr AlKhamissi, Greta Tuckute, Yingtian Tang, et al.*2025 · 11 citations*
18. **[Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://md.research.elamur.ai/free/en/papers/hu-2025-between-circuits-chomsky-pre-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Y. Hu, Jackson Petty, Chuan Shi, et al.*2025 · 9 citations*
19. **[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*
20. **[Language Modeling by Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2025-language-modeling-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junyan Cheng, Peter Clark, Kyle Richardson*2025 · 9 citations*
21. **[ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/loison-2026-vidore-v3-comprehensive-evaluation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**António Loison, Quentin Macé, Antoine Edy, et al.*2026 · 7 citations*
22. **[ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering](https://md.research.elamur.ai/free/en/papers/kaur-2026-chartagent-multimodal-agent-visually-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rachneet Kaur, Nishan Srishankar, Zhen Zeng, et al.*2026 · 5 citations*
23. **[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*
24. **[UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities](https://md.research.elamur.ai/free/en/papers/yeo-2026-universalrag-retrieval-augmented-generation-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Woongyeong Yeo, Kangsan Kim, Soyeong Jeong, et al.*2026 · 4 citations*
25. [**DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arXiv:2609.19969**DeepSeek-AI, Anyi Xu, B. Li, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-1-flash/)
26. **[dLLM: Simple Diffusion Language Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-dllm-simple-diffusion-language-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanhui Zhou, Lingjie Chen, Hanghang Tong, et al.*2026 · 3 citations*
27. [**Baseer: A Vision-Language Model for Arabic Document-to-Markdown OCR arXiv:2509.18174**Khalil Hennara, Muhammad Hreden, Mohamed Motasim Hamed, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-baseer-vision-language-model-arabic/)
28. **[KG-CRAFT: Knowledge Graph-based Contrastive Reasoning with LLMs for Enhancing Automated Fact-checking](https://md.research.elamur.ai/free/en/papers/lourenco-2026-kg-craft-knowledge-graph-based/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Vítor Lourenço, Aline Paes, Tillman Weyde, et al.*2026 · 2 citations*
29. [**Family Matters: Language Transfer and Merging for Adapting Small LLMs to Faroese arXiv:2510.00810**Jenny Kunz, Iben Nyholm Debess, Annika Simonsen*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/kunz-2025-family-matters-language-transfer-merging/)
30. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
31. **[CaTS-Bench: Can Language Models Describe Time Series?](https://md.research.elamur.ai/free/en/papers/zhou-2026-cats-bench-can-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Luca Zhou, Pratham Yashwante, Marshall Fisher, et al.*2026 · 1 citation*
32. **[Structured Entity Extraction from Hawaiian Television Chyrons Using Vision-Language Models](https://md.research.elamur.ai/free/en/papers/lynch-2026-structured-entity-extraction-hawaiian-television/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Kelley Lynch, Owen King, Kyeongmin Rim, et al.*2026 · 1 citation*
33. **[AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages](https://md.research.elamur.ai/free/en/papers/yu-2026-afriquellm-how-data-mixing-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Yu, Tianyi Xu, Michael A. Hedderich, et al.*2026*
34. **[ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents](https://md.research.elamur.ai/free/en/papers/yang-2026-alden-reinforcement-learning-active-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Terry Ruas, Yijun Tian, et al.*2026*
35. **[An Empirical Study of Speculative Decoding for Small Language Models](https://md.research.elamur.ai/free/en/papers/mainardi-2026-empirical-study-speculative-decoding-small/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Luca Mainardi, Selcuk Sandikci, Joaquin Vanschoren*2026*
36. **[Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences](https://md.research.elamur.ai/free/en/papers/padmanabhan-2026-bears-all-bears-some-bears/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sriram Padmanabhan, Siyuan Song, Kanishka Misra*2026*
37. **[Cards Against Contamination: TCG-Bench for Difficulty-Scalable Multilingual LLM Reasoning](https://md.research.elamur.ai/free/en/papers/alrashed-2026-cards-against-contamination-tcg-bench/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sultan AlRashed, Jianghui Wang, Francesco Orabona*2026*
38. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
39. **[Compositional Steering of Large Language Models with Steering Tokens](https://md.research.elamur.ai/free/en/papers/radevski-2026-compositional-steering-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gorjan Radevski, Kiril Gashteovski, Giwon Hong, et al.*2026*
40. **[FedGUI: Benchmarking Federated GUI Agents across Heterogeneous Platforms, Devices, and Operating Systems](https://md.research.elamur.ai/free/en/papers/wang-2026-fedgui-benchmarking-federated-gui-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**WenHao Wang, Haoting Shi, Mengying Yuan, et al.*2026*
41. **[Heterogeneity in Formal Linguistic Competence of Language Models: Is Data the Real Bottleneck?](https://md.research.elamur.ai/free/en/papers/renduchintala-2026-heterogeneity-formal-linguistic-competence-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**H S V N S Kowndinya Renduchintala, Sumit Bhatia*2026*
42. **[Learning to Ask: Multi-Decoder Fine-Tuning for Multi-Hop Visual Question Generation with External Knowledge](https://md.research.elamur.ai/free/en/papers/phukan-2026-learning-ask-multi-decoder-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arpan Phukan, Manish Gupta, Asif Ekbal*2026*
43. **[Offline Preference Optimization via Maximum Marginal Likelihood Estimation](https://md.research.elamur.ai/free/en/papers/najafi-2026-offline-preference-optimization-maximum-marginal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Saeed Najafi, Alona Fyshe*2026*
44. **[PII-VisBench: Evaluating Personally Identifiable Information Safety in Vision Language Models Along a Continuum of Visibility](https://md.research.elamur.ai/free/en/papers/shahariar-2026-pii-visbench-evaluating-personally-identifiable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**G M Shahariar, Zabir Al Nazi, Md Olid Hasan Bhuiyan, et al.*2026*
45. **[Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers](https://md.research.elamur.ai/free/en/papers/shimizu-2026-position-encoding-random-float-sampling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo*2026*
46. **[RABIT: Rationale-Based Distillation Towards Interpretable Automatic Speaking Assessment via a Small Language Model](https://md.research.elamur.ai/free/en/papers/yan-2026-rabit-rationale-based-distillation-interpretable/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Bi-Cheng Yan, Hong-Yun Lin, Fu-An Chao, et al.*2026*
47. **[RoBSA: RoPE-based Blockwise Sparse Multi-head Latent Attention](https://md.research.elamur.ai/free/en/papers/shi-2026-robsa-rope-based-blockwise-sparse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Shi, Kairong Luo, Zhen Zheng, et al.*2026*
48. **[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*
49. **[Specialization without Sparsity: Efficient and Expressive Split-Path Experts for LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-specialization-without-sparsity-efficient-expressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ganghao Liu, Qin Zhou, Zhe Wang, et al.*2026*
50. **[STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*
51. **[SyntaxMind at SemEval-2026 Task 6: Exploring Transformers and LLMs for Unmasking Political Question Evasions](https://md.research.elamur.ai/free/en/papers/riad-2026-syntaxmind-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Md. Shihab Uddin Riad*2026*

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

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