--- title: "Who cites Smaug: Fixing Failure Modes of — 76 citing papers" description: "76 papers of the Elamur Research library cite «Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive», found in their…" canonical: "https://research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Smaug: Fixing Failure Modes of Preference…](https://md.research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/) / cited by # Who cites «Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive» 76 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive»](https://md.research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/) 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. **[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* 3. **[Iterative Reasoning Preference Optimization](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 153 citations* 4. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 152 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/) 5. [**From r to Q*: Your Language Model is Secretly a Q-Function arXiv:2404.12358**Rafael Rafailov, Joey Hejna, Ryan Park, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/rafailov-2024-r-q-language-model-secretly/) 6. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations* 7. [**VinePPO: Refining Credit Assignment in RL Training of LLMs arXiv:2410.01679**Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.*2024 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kazemnejad-2024-vineppo-refining-credit-assignment-rl/) 8. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/) 9. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations* 10. [**Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning arXiv:2407.00782**Zimu Lu, Aojun Zhou, Ke Wang, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-step-controlled-dpo-leveraging-stepwise/) 11. **[Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment](https://md.research.elamur.ai/free/en/papers/oosterlinck-2025-anchored-preference-optimization-contrastive-revisions/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.*2025 · 20 citations* 12. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/) 13. **[From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents](https://md.research.elamur.ai/free/en/papers/tan-2026-coarse-fine-self-adaptive-hierarchical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Tan, Zeyu Zhang, Chen Ma, et al.*2026* 14. **[From Explicit to Implicit: A Theoretical Framework and Transfer Method for Preference Internalization in Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-explicit-implicit-theoretical-framework-transfer/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Binrui Wang, Yongping Du, Yu Pei, et al.*2026* 62 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/) — Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive