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20242026
most citedReinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question Answering

1 citations · 1 across the 10 of their papers we have counts for

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eess.AS2026

MiDashengLM-Gen: Unified Audio Scene Generation via LLM-Driven Autoregressive Flow Matching

Xingwei Sun, Heinrich Dinkel, Gang Li +7

Generating coherent audio scenes that simultaneously blend speech, music, and sound effects remains a significant challenge. Current approaches typically rely on a disjointed pipel…

cs.CV2026

MemoryCard: Topic-Aware Multi-Modal Clue Compression for Long-Video Question Answering

Qing Yang, Pengcheng Huang, Xinze Li +6

Long-video question answering remains challenging for Vision-Language Models (VLMs), as answer-relevant evidence is often sparse, transient, and temporally dispersed across lengthy…

cs.SD2026

Dasheng AudioGen: A Unified Model for Generating Coherent Audio Scenes from Text

Jiahao Mei, Heinrich Dinkel, Yadong Niu +7

Audio generation has long been fragmented, with speech, music, and sound effects produced by domain-specific models that fail to jointly generate coherent audio scenes from a singl…

cs.SD2026

DashengTokenizer: One layer is enough for unified audio understanding and generation

Heinrich Dinkel, Xingwei Sun, Gang Li +8

This paper introduces DashengTokenizer, a continuous audio tokenizer engineered for joint use in both understanding and generation tasks. Unlike conventional approaches, which trai…

eess.AS2026

ACAVCaps: Enabling large-scale training for fine-grained and diverse audio understanding

Yadong Niu, Tianzi Wang, Heinrich Dinkel +6

General audio understanding is a fundamental goal for large audio-language models, with audio captioning serving as a cornerstone task for their development. However, progress in t…