10 papers
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…
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…
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…
MECAT: A Multi-Experts Constructed Benchmark for Fine-Grained Audio Understanding Tasks
Yadong Niu, Tianzi Wang, Heinrich Dinkel +7
While large audio-language models have advanced open-ended audio understanding, they still fall short of nuanced human-level comprehension. This gap persists largely because curren…
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…
MiDashengLM: Efficient Audio Understanding with General Audio Captions
Heinrich Dinkel, Gang Li, Jizhong Liu +7
Current approaches for large audio language models (LALMs) often rely on closed data sources or proprietary models, limiting their generalization and accessibility. This paper intr…