--- title: "Who cites Benchmarking Open-ended Audio — 8 citing papers" description: "8 papers of the Elamur Research library cite «Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Models»…" canonical: "https://research.elamur.ai/free/en/papers/gao-2025-benchmarking-open-ended-audio-dialogue/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/gao-2025-benchmarking-open-ended-audio-dialogue/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Benchmarking Open-ended Audio Dialogue…](https://md.research.elamur.ai/free/en/papers/gao-2025-benchmarking-open-ended-audio-dialogue/) / cited by # Who cites «Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Models» 8 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Models»](https://md.research.elamur.ai/free/en/papers/gao-2025-benchmarking-open-ended-audio-dialogue/) 1. **[Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/yang-2025-holistic-evaluation-large-audio-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chih-Kai Yang, Neo S. Ho, Hung-yi Lee*2025 · 17 citations* 2. **[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* 6 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/gao-2025-benchmarking-open-ended-audio-dialogue/) — Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Models