---
title: "Who cites Generalizing Verifiable Instruction Following"
description: "55 papers of the Elamur Research library cite «Generalizing Verifiable Instruction Following», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/pyatkin-2025-generalizing-verifiable-instruction-following/cited-by/"
---
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# Who cites «Generalizing Verifiable Instruction Following»

55 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · [← back to «Generalizing Verifiable Instruction Following»](https://md.research.elamur.ai/free/en/papers/pyatkin-2025-generalizing-verifiable-instruction-following/)

1. [**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/)
2. [**GLM-5: from Vibe Coding to Agentic Engineering arXiv:2602.15763**Aohan Zeng, Xin Lv, Zhenyu Hou, et al.*2026 · 95 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-5-glm-5-vibe-coding/)
3. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
4. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
5. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
6. **[Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/bae-2026-online-difficulty-filtering-reasoning-oriented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.*2026 · 22 citations*
7. [**Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation arXiv:2603.19220**Zhuolin Yang, Zihan Liu, Yang Chen, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-nemotron-cascade-2-post-training/)
8. **[AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following](https://md.research.elamur.ai/free/en/papers/he-2026-advancedif-rubric-based-benchmarking-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yun He, Wenzhe Li, Hejia Zhang, et al.*2026 · 9 citations*
9. **[RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine Generation](https://md.research.elamur.ai/free/en/papers/li-2026-rubrichub-comprehensive-highly-discriminative-rubric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sunzhu Li, Jiale Zhao, Huimin Ren, et al.*2026 · 9 citations*
10. **[OctoBench: Benchmarking Scaffold-Aware Instruction Following in Repository-Grounded Agentic Coding](https://md.research.elamur.ai/free/en/papers/ding-2026-octobench-benchmarking-scaffold-aware-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ding, Shichun Liu, Enhui Yang, et al.*2026 · 4 citations*
11. **[Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following](https://md.research.elamur.ai/free/en/papers/ren-2026-instructions-are-all-you-need/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Ren, Qianyu He, Powei Chang, et al.*2026 · 3 citations*
12. [**Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale arXiv:2603.25040**Yicheng Zou, Dongsheng Zhu, Lin Zhu, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/zou-2026-intern-s1-pro-scientific/)
13. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
14. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
15. **[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*
16. [**OpenCompass: A Universal Evaluation Platform for Large Language Models arXiv:2605.19276**Maosong Cao, Kai Chen, Haodong Duan, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/cao-2026-opencompass-universal-evaluation-platform/)
17. **[Reasoning Up the Instruction Ladder for Controllable Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-reasoning-up-instruction-ladder-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.*2026 · 1 citation*
18. **[CentaurTA: A Self-Improving Human-Agents Collaboration Framework for Thematic Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-centaurta-self-improving-human-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Wang, Min Huang, Eduard Dragut*2026*
19. **[Complex-IF and Beyond: Expert Rubrics for RLVR](https://md.research.elamur.ai/free/en/papers/mehta-2026-complex-if-beyond-expert-rubrics/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.*2026*
20. **[CSULoRA: Closest Safe Update Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/marchenko-2026-csulora-closest-safe-update-low/) [International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security](https://md.research.elamur.ai/free/en/venues/nlpaics/)**Oleksandr Marchenko, Adelaide Danilov, Aria Nourbakhsh, et al.*2026*
21. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*
22. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
23. [**Qwen3.8-Omni: Towards Native Omni-Modal Agents arXiv:2609.25611**Qwen Team*2026*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-8-omni-native/)
24. **[Verifying the Subjective: Structured Multilingual Rewards for Low-Resource Alignment](https://md.research.elamur.ai/free/en/papers/sha-2026-verifying-subjective-structured-multilingual-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiu Sha, Mengxiao Zhu*2026*

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

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