---
title: "Who cites Jianwen Zhang — 1,066 papers of our library"
description: "1,066 papers of the Elamur Research library cite the works of Jianwen Zhang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Jianwen Zhang

1,088 citations of their works from 1,066 papers of our library (of the 149,439 whose bibliographies we read) · 195 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Jianwen Zhang](https://md.research.elamur.ai/free/en/authors/jianwen-zhang/)

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1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. **[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*
3. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
4. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations*
5. **[K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,019 citations*
6. **[Representing Text for Joint Embedding of Text and Knowledge Bases](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 907 citations*
7. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 761 citations*
8. [**Phi-4 Technical Report arXiv:2412.08905**Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.*2024 · 502 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-4-technical-report/)
9. **[The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.*2024 · 434 citations*
10. **[Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation](https://md.research.elamur.ai/free/en/papers/yamada-2016-joint-learning-embedding-words-entities/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2016 · 428 citations*
11. [**RULER: What's the Real Context Size of Your Long-Context Language Models? arXiv:2404.06654**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 400 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
12. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
13. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
14. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models arXiv:2410.05229**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
15. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
16. **[QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 254 citations*
17. **[CoLAKE: Contextualized Language and Knowledge Embedding](https://md.research.elamur.ai/free/en/papers/sun-2020-colake-contextualized-language-knowledge-embedding/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianxiang Sun, Yunfan Shao, Xipeng Qiu, et al.*2020 · 239 citations*
18. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 216 citations*
19. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
20. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
21. **[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*
22. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model arXiv:2502.02737**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 181 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
23. **[Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 178 citations*
24. [**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/)
25. **[LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding](https://md.research.elamur.ai/free/en/papers/wu-2024-longvideobench-benchmark-long-context-interleaved/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haoning Wu, Dongxu Li, Bei Chen, et al.*2024 · 166 citations*
26. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
27. **[Cross-lingual Wikification Using Multilingual Embeddings](https://md.research.elamur.ai/free/en/papers/tsai-2016-cross-lingual-wikification-multilingual-embeddings/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chen-Tse Tsai, Dan Roth*2016 · 157 citations*
28. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
29. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing arXiv:2406.08464**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
30. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking arXiv:2501.04519**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
31. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
32. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
33. **[STransE: a novel embedding model of entities and relationships in knowledge bases](https://md.research.elamur.ai/free/en/papers/nguyen-2016-stranse-novel-embedding-model-entities/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, et al.*2016 · 130 citations*
34. **[Learning Distributed Representations of Texts and Entities from Knowledge Base](https://md.research.elamur.ai/free/en/papers/yamada-2017-learning-distributed-representations-texts-entities/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2017 · 125 citations*
35. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
36. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
37. [**Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks arXiv:2404.02151**Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/andriushchenko-2024-jailbreaking-leading-safety-aligned-llms/)
38. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
39. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations*
40. **[A Careful Examination of Large Language Model Performance on Grade School Arithmetic](https://md.research.elamur.ai/free/en/papers/zhang-2024-careful-examination-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugh Zhang, Jeff Da, Dean Lee, et al.*2024 · 101 citations*
41. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 99 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
42. [**LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory arXiv:2410.10813**Di Wu, Hongwei Wang, Wenhao Yu, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-longmemeval-benchmarking-chat-assistants-long/)
43. [**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/)
44. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
45. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
46. [**Liger Kernel: Efficient Triton Kernels for LLM Training arXiv:2410.10989**Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/hsu-2024-liger-kernel-efficient-triton-kernels/)
47. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
48. [**Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers arXiv:2408.06195**Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/)
49. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
50. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
51. [**LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs arXiv:2408.07055**Yushi Bai, Jiajie Zhang, Xin Lv, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longwriter-unleashing-10-000/)
52. **[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*
53. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
54. [**Phi-4-reasoning Technical Report arXiv:2504.21318**Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2025-phi-4-reasoning-technical-report/)
55. [**ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models arXiv:2402.11684**Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-allava-harnessing-gpt4v-synthesized-data/)
56. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations*
57. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
58. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/)
59. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
60. **[Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors](https://md.research.elamur.ai/free/en/papers/maurya-2025-unifying-ai-tutor-evaluation-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kaushal Kumar Maurya, Kv Aditya Srivatsa, Kseniia Petukhova, et al.*2025 · 53 citations*
61. **[From Word Types to Tokens and Back: A Survey of Approaches to Word Meaning Representation and Interpretation](https://md.research.elamur.ai/free/en/papers/apidianaki-2023-word-types-tokens-back-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Marianna Apidianaki*2023 · 49 citations*
62. **[WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines](https://md.research.elamur.ai/free/en/papers/winata-2025-worldcuisines-massive-scale-benchmark-multilingual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan, et al.*2025 · 46 citations*
63. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
64. **[CompAct: Compressing Retrieved Documents Actively for Question Answering](https://md.research.elamur.ai/free/en/papers/yoon-2024-compact-compressing-retrieved-documents-actively/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chanwoong Yoon, Taewhoo Lee, Hyeon Hwang, et al.*2024 · 34 citations*
65. [**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/)
66. [**DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs arXiv:2503.07067**Jongwoo Ko, Tianyi Chen, Sungnyun Kim, et al.*2025 · 32 citations*](https://md.research.elamur.ai/free/en/papers/ko-2025-distillm-2-contrastive-approach-boosts/)
67. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)
68. **[Contextualization Distillation from Large Language Model for Knowledge Graph Completion](https://md.research.elamur.ai/free/en/papers/li-2024-contextualization-distillation-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dawei Li, Zhen Tan, Tianlong Chen, et al.*2024 · 30 citations*
69. **[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*
70. [**Distillation Scaling Laws arXiv:2502.08606**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
71. **[MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Zhou, Yongping Xiong, Zheng Liu, et al.*2025 · 26 citations*
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74. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
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77. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
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92. [**Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle arXiv:2407.13833**Emman Haider, Daniel Perez-Becker, Thomas Portet, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/haider-2024-phi-3-safety-post-training/)
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