---
title: "Who cites IOPO: Empowering LLMs with — 14 citing papers"
description: "14 papers of the Elamur Research library cite «IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference…"
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---
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# Who cites «IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization»

14 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization»](https://md.research.elamur.ai/free/en/papers/zhang-2025-iopo-empowering-llms-complex-instruction/)

1. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
2. **[Internal Chain-of-Thought: Empirical Evidence for Layer-wise Subtask Scheduling in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-internal-chain-thought-empirical-evidence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhipeng Yang, Junzhuo Li, Siyu Xia, et al.*2025 · 7 citations*
3. **[EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2025-eifbench-extremely-complex-instruction-following/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Zou, Xinghua Zhang, Haiyang Yu, et al.*2025 · 5 citations*
4. **[MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models](https://md.research.elamur.ai/free/en/papers/ye-2026-muldimif-multi-dimensional-constraint-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Caishuang Huang, Zhuohan Chen, et al.*2026 · 4 citations*
5. **[IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-critic-fine-grained-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
6. **[IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-rewardbench-benchmarking-judge-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*

8 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2025-iopo-empowering-llms-complex-instruction/) — IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization