--- title: "Who cites Ding Ding — 55 papers of our library" description: "55 papers of the Elamur Research library cite the works of Ding Ding, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/ding-ding/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ding-ding/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Ding Ding](https://md.research.elamur.ai/free/en/authors/ding-ding/) / cited by # Who cites Ding Ding 55 citations of their works from 55 papers of our library (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · [← Ding Ding](https://md.research.elamur.ai/free/en/authors/ding-ding/) 1. [**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/) 2. [**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/) 3. **[Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models](https://md.research.elamur.ai/free/en/papers/chen-2026-dual-axis-generative-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Chen, Shengpeng Ji, Zhengqing Liu, et al.*2026 · 4 citations* 4. **[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* 5. **[Closing the Modality Reasoning Gap for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-closing-modality-reasoning-gap-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoren Wang, Heng Lu, Xueyao Zhang, et al.*2026 · 2 citations* 6. **[Do We Need Distinct Representations for Every Speech Token? Unveiling and Exploiting Redundancy in Large Speech Language Models](https://md.research.elamur.ai/free/en/papers/xiang-2026-do-we-need-distinct-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bajian Xiang, Tingwei Guo, Xuan Chen, et al.*2026 · 2 citations* 7. **[Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-discovering-causally-validating-emotion-sensitive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiutian Zhao, Björn Schuller, Berrak Sisman*2026 · 1 citation* 8. **[From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models](https://md.research.elamur.ai/free/en/papers/tong-2026-static-inference-dynamic-interaction-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junlong Tong, Zilong Wang, YuJie Ren, et al.*2026 · 1 citation* 9. **[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* 10. **[Afrispeech Semantics: Evaluating Audio–Semantic Reasoning in Spoken Language Models Across Domains and Accents](https://md.research.elamur.ai/free/en/papers/okocha-2026-afrispeech-semantics-evaluating-audio-semantic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chibuzor Okocha, Christan Grant*2026* 11. **[Don't Just Listen, Try Planning: Graph-based Retrieval-Generation Agent for Long-form Audio Meeting Understanding](https://md.research.elamur.ai/free/en/papers/tang-2026-don-t-just-listen-try/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Quanwei Tang, Dong Zhang, Shoushan Li, et al.*2026* 12. **[Evaluating the Expressive Appropriateness of Speech in Rich Contexts](https://md.research.elamur.ai/free/en/papers/wang-2026-evaluating-expressive-appropriateness-speech-rich/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianrui Wang, Ziyang Ma, Yizhou Peng, et al.*2026* 13. **[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* 14. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026* 15. **[Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/sheng-2026-think-smart-not-hard-difficulty/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Sheng, Shilin Zhou, Chen Gong, et al.*2026* 16. **[UniSRM: A Unified Speech Reward Model for Reasoning-Based Fine-grained Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-unisrm-unified-speech-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanyuan Wang, Dongchao Yang, Yayue Deng, et al.*2026* 39 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/ding-ding/) — Ding Ding