---
title: "Who cites Peng Liu — 112 papers of our library"
description: "112 papers of the Elamur Research library cite the works of Peng Liu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/peng-liu/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/peng-liu/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Peng Liu](https://md.research.elamur.ai/free/en/authors/peng-liu/) / cited by

# Who cites Peng Liu

120 citations of their works from 112 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Peng Liu](https://md.research.elamur.ai/free/en/authors/peng-liu/)

1. [**Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paper**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
2. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
3. [**ToolRL: Reward is All Tool Learning Needs arXiv:2504.13958**Cheng Qian, Emre Can Acikgoz, Qi He, et al.*2025 · 94 citations*](https://md.research.elamur.ai/free/en/papers/qian-2025-toolrl-reward-all-tool-learning/)
4. [**Kimi-Audio Technical Report arXiv:2504.18425**KimiTeam, Ding Ding, Zeqian Ju, et al.*2025 · 57 citations*](https://md.research.elamur.ai/free/en/papers/kimiteam-2025-kimi-audio-technical-report/)
5. [**SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models arXiv:2504.11468**Hardy Chen, Haoqin Tu, Fali Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-sft-rl-early-investigation-training/)
6. [**Step-Audio 2 Technical Report arXiv:2507.16632**Boyong Wu, Chao Yan, Chen Hu, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-step-audio-2-technical/)
7. [**MiMo-Audio: Audio Language Models are Few-Shot Learners arXiv:2512.23808**Xiaomi LLM-Core Team, Dong Zhang, Gang Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)
8. **[R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning](https://md.research.elamur.ai/free/en/papers/he-2026-r1-t1-fully-incentivizing-translation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Minggui He, Yilun Liu, Shimin Tao, et al.*2026 · 22 citations*
9. [**Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning arXiv:2505.15154**Jinghui Lu, Haiyang Yu, Siliang Xu, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/lu-2025-prolonged-reasoning-all-need-certainty/)
10. **[NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2025-nover-incentive-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Liu, Siya Qi, Xinyu Wang, et al.*2025 · 7 citations*
11. [**MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction arXiv:2604.27393**Junbo Cui, Bokai Xu, Chongyi Wang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cui-2026-minicpm-o-4-5/)
12. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
13. **[Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/lei-2026-writing-rl-advancing-long-form/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanyu Lei, Chenliang Li, Yuning Wu, et al.*2026 · 4 citations*
14. **[XY-Tokenizer: Mitigating the Semantic-Acoustic Conflict in Low-Bitrate Speech Codecs](https://md.research.elamur.ai/free/en/papers/gong-2026-xy-tokenizer-mitigating-semantic-acoustic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yitian Gong, Luozhijie Jin, Kuangwei Chen, et al.*2026 · 4 citations*
15. **[Chronological Thinking in Full-Duplex Spoken Dialogue Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-chronological-thinking-full-duplex-spoken/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Donghang Wu, Haoyang Zhang, Chen Chen, et al.*2026 · 3 citations*
16. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations*
17. [**Step-Audio-R1 Technical Report arXiv:2511.15848**Fei Tian, Xiangyu Tony Zhang, Yuxin Zhang, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/tian-2025-step-audio-r1-technical/)
18. **[AdaTooler-V: Adaptive Tool-Use for Images and Videos](https://md.research.elamur.ai/free/en/papers/wang-2026-adatooler-v-adaptive-tool-use/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chaoyang Wang, Kaituo Feng, Dongyang Chen, et al.*2026 · 2 citations*
19. **[Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic](https://md.research.elamur.ai/free/en/papers/ma-2026-timely-machine-awareness-time-makes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichuan Ma, Linyang Li, Yongkang Chen, et al.*2026 · 2 citations*
20. **[Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chart-rl-generalized-chart-comprehension/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Xin Zhang, Xingyu Li, Rongguang Wang, et al.*2026 · 1 citation*
21. **[Inferring Events from Time Series using Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-inferring-events-time-series-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingtian Tan, Mike A Merrill, Zachary Gottesman, et al.*2026 · 1 citation*
22. **[SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-see-signal-embedding-energy-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanhe Zhang, Jiayu Tian, Yibo Zhang, et al.*2026 · 1 citation*
23. **[UltraEval-Audio: A Unified Framework for Comprehensive Evaluation of Audio Foundation Models](https://md.research.elamur.ai/free/en/papers/shi-2026-ultraeval-audio-unified-framework-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qundong Shi, Jie Zhou, Biyuan Lin, et al.*2026 · 1 citation*
24. **[Visually-Guided Policy Optimization for Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-visually-guided-policy-optimization-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zengbin Wang, Feng Xiong, Liang Lin, et al.*2026 · 1 citation*
25. **[BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-batonvoice-operationalist-framework-enhancing-controllable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Wang, Ruotian Ma, Xingyu Chen, et al.*2026*
26. **[Beyond Sentence-level Labels: Integrating Conversational Context and Personal Experience for Natural Emotional Expression](https://md.research.elamur.ai/free/en/papers/sun-2026-beyond-sentence-level-labels-integrating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Sun, Chenyang Le, Wei Wang, et al.*2026*
27. **[Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-transcription-unified-audio-schema/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linhao Zhang, Yuhan Song, Aiwei Liu, et al.*2026*
28. **[ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding](https://md.research.elamur.ai/free/en/papers/zhao-2026-chemvlr-prioritizing-reasoning-perception-chemical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanle Zhao, Xinyuan Cai, Xiang Cheng, et al.*2026*
29. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
30. **[HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-halluaudio-comprehensive-benchmark-hallucination-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiyu Zhao, Yiming Chen, Wenhuan Lu, et al.*2026*
31. **[HearSay Benchmark: Do Audio LLMs Leak What They Hear?](https://md.research.elamur.ai/free/en/papers/wang-2026-hearsay-benchmark-do-audio-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Wang, Kaiwen Luo, Liang Lin, et al.*2026*
32. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
33. **[On-policy Reinforcement Fine-tuning with Offline reward for Multi-step Embodied Planning](https://md.research.elamur.ai/free/en/papers/wu-2026-policy-reinforcement-fine-tuning-offline/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Di Wu, Jiaxin Fan, Chloe Gu, et al.*2026*
34. **[Protecting Bystander Privacy via Selective Hearing in Audio LLMs](https://md.research.elamur.ai/free/en/papers/zhan-2026-protecting-bystander-privacy-selective-hearing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Zhan, Guangzhi Sun, Jose Such, et al.*2026*
35. **[RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios](https://md.research.elamur.ai/free/en/papers/zhang-2026-rsa-bench-benchmarking-audio-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Zhang, Kaiwen Luo, Liang Lin, et al.*2026*
36. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
37. **[UniCM: A Unified Consistency Model For Efficient Multimodal Generation and Understanding](https://md.research.elamur.ai/free/en/papers/xu-2026-unicm-unified-consistency-model-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenkai Xu, Xu Wang, Zhenyi Liao, et al.*2026*
38. **[WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem](https://md.research.elamur.ai/free/en/papers/wang-2026-wenetspeech-wu-datasets-benchmarks-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengyou Wang, Mingchen Shao, Jingbin Hu, et al.*2026*

74 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/peng-liu/) — Peng Liu