---
title: "Who cites Dacheng Li — 3,560 papers of our library"
description: "3,560 papers of the Elamur Research library cite the works of Dacheng Li, found in their bibliographies · page 1 of 8 · 1–100; the most cited first."
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---
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# Who cites Dacheng Li

3,761 citations of their works from 3,560 papers of our library (of the 149,439 whose bibliographies we read) · 775 with a page here, the most cited first · page 1 of 8 · 1–100 · [← Dacheng Li](https://md.research.elamur.ai/free/en/authors/dacheng-li/)

**1** [2](https://md.research.elamur.ai/free/en/authors/dacheng-li/cited-by/page/2/) … [8](https://md.research.elamur.ai/free/en/authors/dacheng-li/cited-by/page/8/) [next →](https://md.research.elamur.ai/free/en/authors/dacheng-li/cited-by/page/2/)

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. **[DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-r1-incentivizing-reasoning-capability/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**DeepSeek-AI, Daya Guo, Dejian Yang, et al.*2025 · 4,728 citations*
3. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-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/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
4. **[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*
5. **[Improved Baselines with Visual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/) [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/)**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,614 citations*
6. **[G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Dan Iter, Yichong Xu, et al.*2023 · 2,000 citations*
7. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone arXiv:2404.14219**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,134 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
8. **[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*
9. [**Universal and Transferable Adversarial Attacks on Aligned Language Models arXiv:2307.15043**Andy Zou, Zifan Wang, Nicholas Carlini, et al.*2023 · 1,005 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-universal-transferable-adversarial-attacks-aligned/)
10. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
11. **[MMBench: Is Your Multi-modal Model an All-around Player?](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 942 citations*
12. **[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*
13. **[WizardLM: Empowering large pre-trained language models to follow complex instructions](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 741 citations*
14. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
15. [**Instruction-Following Evaluation for Large Language Models arXiv:2311.07911**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 615 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
16. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 559 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
17. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 553 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
18. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
19. [**Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference arXiv:2403.04132**Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.*2024 · 546 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2024-chatbot-arena-open-platform-evaluating/)
20. **[How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 541 citations*
21. **[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*
22. [**LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding arXiv:2308.14508**Yushi Bai, Xin Lv, Jiajie Zhang, et al.*2023 · 514 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-longbench-bilingual-multitask-benchmark/)
23. [**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/)
24. **[Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations](https://md.research.elamur.ai/free/en/papers/wang-2024-math-shepherd-verify-reinforce-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiyi Wang, Lei Li, Zhihong Shao, et al.*2024 · 497 citations*
25. **[Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/) [Proceedings of the VLDB Endowment](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-vldb-endowment/)**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 463 citations*
26. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 456 citations*
27. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
28. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks arXiv:2312.14238**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 435 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
29. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
30. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
31. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
32. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
33. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*
34. **[VILA: On Pre-training for Visual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/) [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/)**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 381 citations*
35. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
36. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
37. [**ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate arXiv:2308.07201**Chi-Min Chan, Weize Chen, Yusheng Su, et al.*2023 · 359 citations*](https://md.research.elamur.ai/free/en/papers/chan-2023-chateval-better-llm-based/)
38. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
39. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
40. [**Textbooks Are All You Need II: phi-1.5 technical report arXiv:2309.05463**Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 336 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-textbooks-all-need-ii-phi/)
41. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
42. **[Multi-step Jailbreaking Privacy Attacks on ChatGPT](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 304 citations*
43. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
44. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning arXiv:2309.05653**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
45. **[HuatuoGPT, Towards Taming Language Model to Be a Doctor](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongbo Zhang, Junying Chen, Feng Jiang, et al.*2023 · 282 citations*
46. [**Prometheus: Inducing Fine-grained Evaluation Capability in Language Models arXiv:2310.08491**Seungone Kim, Jamin Shin, Yejin Cho, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/)
47. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads arXiv:2401.10774**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/)
48. **[JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/chao-2024-jailbreakbench-open-robustness-benchmark-jailbreaking/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.*2024 · 277 citations*
49. **[LLM-QAT: Data-Free Quantization Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 276 citations*
50. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools arXiv:2405.20362**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
51. [**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/)
52. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
53. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
54. **[InternVideo2: Scaling Foundation Models for Multimodal Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 253 citations*
55. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset arXiv:2309.11998**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
56. [**WildChat: 1M ChatGPT Interaction Logs in the Wild arXiv:2405.01470**Wenting Zhao, Xiang Ren, Jack Hessel, et al.*2024 · 239 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-wildchat-1m-chatgpt-interaction-logs/)
57. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 237 citations*
58. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
59. [**Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models arXiv:2405.01535**Seungone Kim, Juyoung Suk, Shayne Longpre, et al.*2024 · 234 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/)
60. [**GAIA: a benchmark for General AI Assistants arXiv:2311.12983**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
61. [**AlpaGasus: Training A Better Alpaca with Fewer Data arXiv:2307.08701**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/)
62. **[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*
63. [**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/)
64. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
65. [**DeepSeek-VL: Towards Real-World Vision-Language Understanding arXiv:2403.05525**Haoyu Lu, Wen Liu, Bo Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-deepseek-vl-real-world/)
66. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty arXiv:2401.15077**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)
67. **[RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 207 citations*
68. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 arXiv:2311.10702**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
69. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
70. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
71. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
72. [**OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models arXiv:2308.13137**Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, et al.*2023 · 195 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-omniquant-omnidirectionally-calibrated-quantization-large/)
73. **[InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhan-2024-injecagent-benchmarking-indirect-prompt-injections/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiusi Zhan, Zhixiang Liang, Zifan Ying, et al.*2024 · 193 citations*
74. **[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*
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76. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models arXiv:2310.00746**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
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78. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
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84. [**Aligning Large Multimodal Models with Factually Augmented RLHF arXiv:2309.14525**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 176 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
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93. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
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97. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
98. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models arXiv:2307.11088**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/)
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100. **[Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Antoine Louis, Gijs van Dijck, Gerasimos Spanakis*2023 · 157 citations*

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