1 citations · 1 across the 7 of their papers we have counts for
9 papers
EEG-Captioner: Grounding EEG-to-Language Generation in Fundamental Signal Properties
Leyuan Jin, Jiahao Mei, Yixuan Yuan +3
Electroencephalography (EEG)-to-language models offer a promising approach for translating complex neural signals into human-readable descriptions. However, generating plausible la…
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…
MMAG: A Multi-Control Mixed Audio Generation Benchmark
Zihao Zheng, Xuenan Xu, Jiahao Mei +5
Recent audio generation systems have progressed from single-modality synthesis to generating complex acoustic scenes containing speech, music, and sound effects. Therefore, evaluat…
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…
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…
LARA-Gen: Enabling Continuous Emotion Control for Music Generation Models via Latent Affective Representation Alignment
Jiahao Mei, Xuenan Xu, Shimeng Li +7
Recent advances in text-to-music models have enabled coherent music generation from text prompts, yet fine-grained emotional control remains unresolved. We introduce LARA-Gen, a fr…
UniFlow-Audio: Unified Flow Matching for Audio Generation from Omni-Modalities
Xuenan Xu, Jiahao Mei, Zihao Zheng +9
Audio generation, including speech, music and sound effects, has advanced rapidly in recent years. These tasks can be divided into two categories: time-aligned (TA) tasks, where ea…
MM-StoryAgent: Immersive Narrated Storybook Video Generation with a Multi-Agent Paradigm across Text, Image and Audio
Xuenan Xu, Jiahao Mei, Chenliang Li +5
The rapid advancement of large language models (LLMs) and artificial intelligence-generated content (AIGC) has accelerated AI-native applications, such as AI-based storybooks that…
WritingBench: A Comprehensive Benchmark for Generative Writing
Yuning Wu, Jiahao Mei, Ming Yan +8
Recent advancements in large language models (LLMs) have significantly enhanced text generation capabilities, yet evaluating their performance in generative writing remains a chall…