---
title: "Who cites Zhijie Yan — 276 papers of our library"
description: "276 papers of the Elamur Research library cite the works of Zhijie Yan, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/zhijie-yan/cited-by/"
---
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# Who cites Zhijie Yan

338 citations of their works from 276 papers of our library (of the 149,439 whose bibliographies we read) · 84 with a page here, the most cited first · [← Zhijie Yan](https://md.research.elamur.ai/free/en/authors/zhijie-yan/)

1. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
2. [**Qwen2-Audio Technical Report arXiv:2407.10759**Yunfei Chu, Jin Xu, Qian Yang, et al.*2024 · 238 citations*](https://md.research.elamur.ai/free/en/papers/chu-2024-qwen2-audio-technical-report/)
3. [**Qwen2.5-Omni Technical Report arXiv:2503.20215**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 227 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
4. **[F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching](https://md.research.elamur.ai/free/en/papers/chen-2025-f5-tts-fairytaler-that-fakes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushen Chen, Zhikang Niu, Ziyang Ma, et al.*2025 · 152 citations*
5. [**VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs arXiv:2406.07476**Zesen Cheng, Sicong Leng, Hang Zhang, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-videollama-2-advancing-spatial-temporal/)
6. [**Qwen3-Omni Technical Report arXiv:2509.17765**Jin Xu, Zhifang Guo, Hangrui Hu, et al.*2025 · 117 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen3-omni-technical-report/)
7. **[AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension](https://md.research.elamur.ai/free/en/papers/yang-2024-air-bench-benchmarking-large-audio/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Yang, Jin Xu, Wenrui Liu, et al.*2024 · 112 citations*
8. [**CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models arXiv:2412.10117**Zhihao Du, Yuxuan Wang, Qian Chen, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/du-2024-cosyvoice-2-scalable-streaming-speech/)
9. [**LLaMA-Omni: Seamless Speech Interaction with Large Language Models arXiv:2409.06666**Qingkai Fang, Shoutao Guo, Yan Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/fang-2024-llama-omni-seamless-speech-interaction/)
10. **[GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities](https://md.research.elamur.ai/free/en/papers/ghosh-2024-gama-large-audio-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sreyan Ghosh, Sonal Kumar, Ashish Seth, et al.*2024 · 87 citations*
11. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
12. **[VoiceBench: Benchmarking LLM-Based Voice Assistants](https://md.research.elamur.ai/free/en/papers/chen-2026-voicebench-benchmarking-llm-based-voice/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yiming Chen, Xianghu Yue, Chen Zhang, et al.*2026 · 74 citations*
13. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations*
14. [**MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark arXiv:2410.19168**S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/sakshi-2024-mmau-massive-multi-task-audio/)
15. [**GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot arXiv:2412.02612**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-glm-4-voice-intelligent/)
16. [**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/)
17. [**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/)
18. [**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/)
19. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
20. **[OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation](https://md.research.elamur.ai/free/en/papers/zhang-2025-omniflatten-end-end-gpt-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinglin Zhang, Luyao Cheng, Chong Deng, et al.*2025 · 27 citations*
21. **[Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xie Zhifei, Mingbao Lin, Zihang Liu, et al.*2025 · 25 citations*
22. **[Autoregressive Speech Synthesis without Vector Quantization](https://md.research.elamur.ai/free/en/papers/meng-2025-autoregressive-speech-synthesis-without-vector/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingwei Meng, Long Zhou, Shujie Liu, et al.*2025 · 25 citations*
23. [**Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction arXiv:2502.11946**Ailin Huang, Boyong Wu, Bruce Wang, et al.*2025 · 25 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-step-audio-unified-understanding/)
24. **[WavRAG: Audio-Integrated Retrieval Augmented Generation for Spoken Dialogue Models](https://md.research.elamur.ai/free/en/papers/chen-2025-wavrag-audio-integrated-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Chen, Shengpeng Ji, Haoxiao Wang, et al.*2025 · 22 citations*
25. **[LLaMA-Omni 2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis](https://md.research.elamur.ai/free/en/papers/fang-2025-llama-omni-2-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingkai Fang, Yan Zhou, Shoutao Guo, et al.*2025 · 20 citations*
26. **[Distilling an End-to-End Voice Assistant Without Instruction Training Data](https://md.research.elamur.ai/free/en/papers/held-2025-distilling-end-end-voice-assistant/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Held, Yanzhe Zhang, Minzhi Li, et al.*2025 · 18 citations*
27. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/)
28. **[OmniBench: Towards The Future of Universal Omni-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-omnibench-towards-future-universal-omni/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yizhi Li, Yinghao Ma, Ge Zhang, et al.*2024 · 17 citations*
29. [**Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction arXiv:2502.17239**Tianpeng Li, Jun Liu, Tao Zhang, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-audio-unified-framework/)
30. [**Qwen3-TTS Technical Report arXiv:2601.15621**Hangrui Hu, Xinfa Zhu, Ting He, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hu-2026-qwen3-tts-technical-report/)
31. [**Scaling Speech-Text Pre-training with Synthetic Interleaved Data arXiv:2411.17607**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-speech-text-pre-training/)
32. **[Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation](https://md.research.elamur.ai/free/en/papers/kim-2024-paralinguistics-aware-speech-empowered-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, et al.*2024 · 13 citations*
33. **[QualiSpeech: A Speech Quality Assessment Dataset with Natural Language Reasoning and Descriptions](https://md.research.elamur.ai/free/en/papers/wang-2025-qualispeech-speech-quality-assessment-dataset/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siyin Wang, Wenyi Yu, Xianzhao Chen, et al.*2025 · 12 citations*
34. **[VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models](https://md.research.elamur.ai/free/en/papers/cui-2025-voxeval-benchmarking-knowledge-understanding-capabilities/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Xiaoqi Jiao, Ziqiao Meng, et al.*2025 · 9 citations*
35. [**Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models arXiv:2501.01034**Bin Wang, Xunlong Zou, Shuo Sun, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-advancing-singlish-understanding-bridging-gap/)
36. [**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/)
37. **[VoiceStar: Robust Zero-Shot Autoregressive TTS with Duration Control and Extrapolation](https://md.research.elamur.ai/free/en/papers/peng-2026-voicestar-robust-zero-shot-autoregressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Puyuan Peng, Zhisheng Zheng, Shang-Wen Li, et al.*2026 · 4 citations*
38. **[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*
39. [**NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speech arXiv:2507.13155**Maksim Borisov, Egor Spirin, Daria Diatlova*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/borisov-2025-nonverbaltts-public-english-corpus-text/)
40. **[Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-audio-jailbreak-open-comprehensive-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zirui Song, Qian Jiang, Mingxuan Cui, et al.*2026 · 3 citations*
41. **[SpeechLLM-as-Judges: Towards General and Interpretable Speech Quality Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-speechllm-as-judges-general-interpretable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wang, Jinghua Zhao, Yifan Yang, et al.*2026 · 3 citations*
42. **[ZipVoice-Dialog: Non-Autoregressive Spoken Dialogue Generation with Flow Matching](https://md.research.elamur.ai/free/en/papers/zhu-2026-zipvoice-dialog-non-autoregressive-spoken/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Zhu, Wei Kang, Liyong Guo, et al.*2026 · 3 citations*
43. **[Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World](https://md.research.elamur.ai/free/en/papers/sadasivan-2026-attacker-s-noise-can-manipulate/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Vinu Sankar Sadasivan, Soheil Feizi, Rajiv Mathews, et al.*2026 · 2 citations*
44. **[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*
45. **[Efficient Training for Cross-lingual Speech Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-efficient-training-cross-lingual-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yan Zhou, Qingkai Fang, Yun Hong, et al.*2026 · 2 citations*
46. [**Habibi: Laying the Open-Source Foundation of Unified-Dialectal Arabic Speech Synthesis arXiv:2601.13802**Yushen Chen, Junzhe Liu, Yujie Tu, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/chen-2026-habibi-laying-open-source-foundation/)
47. **[LLM-ForcedAligner: A Non-Autoregressive and Accurate LLM-Based Forced Aligner for Multilingual and Long-Form Speech](https://md.research.elamur.ai/free/en/papers/mu-2026-llm-forcedaligner-non-autoregressive-accurate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bingshen Mu, Xian Shi, Xiong Wang, et al.*2026 · 2 citations*
48. [**MENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs arXiv:2602.07036**Zien Sheikh Ali, Hunzalah Hassan Bhatti, Rabindra Nath Nandi, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-menaspeechbank-reference-voice-bank-persona/)
49. **[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*
50. **[HumMusQA: A Human-written Music Understanding QA Benchmark Dataset](https://md.research.elamur.ai/free/en/papers/weck-2026-hummusqa-human-written-music-understanding/) [Workshop on NLP for Music and Audio](https://md.research.elamur.ai/free/en/venues/nlp4musa/)**Benno Weck, Pablo Puentes, Andrea Poltronieri, et al.*2026 · 1 citation*
51. **[Language Family Matters: Evaluating SpeechLLMs Across Linguistic Boundaries](https://md.research.elamur.ai/free/en/papers/zhang-2026-language-family-matters-evaluating-speechllms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuchen Zhang, Ravi Shekhar, Haralambos Mouratidis*2026 · 1 citation*
52. **[Omni-Embed-Audio: Leveraging Multimodal LLMs for Robust Audio-Text Retrieval](https://md.research.elamur.ai/free/en/papers/yoo-2026-omni-embed-audio-leveraging-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**HaeJun Yoo, Yongseop Shin, Insung Lee, et al.*2026 · 1 citation*
53. **[Rubric-Guided Fine-tuning of SpeechLLMs for Multi-Aspect, Multi-Rater L2 Reading-Speech Assessment](https://md.research.elamur.ai/free/en/papers/parikh-2026-rubric-guided-fine-tuning-speechllms/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aditya Kamlesh Parikh, Cristian Tejedor-García, Catia Cucchiarini, et al.*2026 · 1 citation*
54. **[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*
55. **[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*
56. **[UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions](https://md.research.elamur.ai/free/en/papers/qiang-2026-unisonate-unified-model-speech-music/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chunyu Qiang, Xiaopeng Wang, Kang Yin, et al.*2026 · 1 citation*
57. **[Unlocking Large Audio-Language Models for Interactive Language Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-unlocking-large-audio-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongfu Liu, Zhouying Cui, Xiangming Gu, et al.*2026 · 1 citation*
58. **[AEQ-Bench: Measuring Empathy of Omni-Modal Large Models](https://md.research.elamur.ai/free/en/papers/luo-2026-aeq-bench-measuring-empathy-omni/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Lewei Yao, Lanqing Hong, et al.*2026*
59. **[AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling](https://md.research.elamur.ai/free/en/papers/shi-2026-affectcodec-emotion-preserving-neural-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Shi, Hongfei Du, Xinyuan Song, et al.*2026*
60. **[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*
61. **[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*
62. **[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*
63. [**CodecMOS-Accent: A MOS Benchmark of Resynthesized and TTS Speech from Neural Codecs Across English Accents arXiv:2603.14328**Wen-Chin Huang, Nicholas Sanders, Erica Cooper*2026*](https://md.research.elamur.ai/free/en/papers/huang-2026-codecmos-accent-mos-benchmark-resynthesized/)
64. **[Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios](https://md.research.elamur.ai/free/en/papers/pan-2026-comprehensive-benchmarking-long-form-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changhao Pan, Rui Yang, Han Wang, et al.*2026*
65. **[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*
66. **[F-Actor: Controllable Conversational Behavior in Full-Duplex Models](https://md.research.elamur.ai/free/en/papers/zufle-2026-f-actor-controllable-conversational-behavior/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Maike Züfle, Ondrej Klejch, Nicholas Sanders, et al.*2026*
67. **[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*
68. **[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*
69. **[ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment](https://md.research.elamur.ai/free/en/papers/yun-2026-immersivetts-environment-aware-text-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun-Hak Yun, Seung-Bin Kim, Seong-Whan Lee*2026*
70. [**Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs arXiv:2601.12494**Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury*2026*](https://md.research.elamur.ai/free/en/papers/bhatti-2026-multi-task-instruction-tuning-data/)
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84. [**Phir Hera Fairy: An English Fairytaler is a Strong Faker of Fluent Speech in Low-Resource Indian Languages arXiv:2505.20693**Praveen Srinivasa Varadhan, Srija Anand, Soma Siddhartha, et al.*2025*](https://md.research.elamur.ai/free/en/papers/varadhan-2025-phir-hera-fairy-english-fairytaler/)

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