17 citations · 47 across the 35 of their papers we have counts for
19 papers · 1 filter
SINGER: Vivid Audio-driven Singing Video Generation with Multi-scale Spectral Diffusion Model
Yan Li, Ziya Zhou, Zhiqiang Wang +3
Recent advancements in generative models have significantly enhanced talking face video generation, yet singing video generation remains underexplored. The differences between huma…
Foundation Cures Personalization: Improving Personalized Models' Prompt Consistency via Hidden Foundation Knowledge
Yiyang Cai, Zhengkai Jiang, Yulong Liu +4
Facial personalization faces challenges to maintain identity fidelity without disrupting the foundation model's prompt consistency. The mainstream personalization models employ ide…
Both Ears Wide Open: Towards Language-Driven Spatial Audio Generation
Peiwen Sun, Sitong Cheng, Xiangtai Li +5
Recently, diffusion models have achieved great success in mono-channel audio generation. However, when it comes to stereo audio generation, the soundscapes often have a complex sce…
PSHuman: Photorealistic Single-image 3D Human Reconstruction using Cross-Scale Multiview Diffusion and Explicit Remeshing
Peng Li, Wangguandong Zheng, Yuan Liu +9
Detailed and photorealistic 3D human modeling is essential for various applications and has seen tremendous progress. However, full-body reconstruction from a monocular RGB image r…
NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models
Cheng Lin, Lujun Li, Dezhi Li +3
In this paper, we introduce Nested Low-Rank Adaptation (NoRA), a novel approach to parameter-efficient fine-tuning that extends the capabilities of Low-Rank Adaptation (LoRA) techn…
Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model
Zhen Ye, Peiwen Sun, Jiahe Lei +9
Recent advancements in audio generation have been significantly propelled by the capabilities of Large Language Models (LLMs). The existing research on audio LLM has primarily focu…
STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs
Peijie Dong, Lujun Li, Yuedong Zhong +8
In this paper, we present the first structural binarization method for LLM compression to less than 1-bit precision. Although LLMs have achieved remarkable performance, their memor…
Can LLMs "Reason" in Music? An Evaluation of LLMs' Capability of Music Understanding and Generation
Ziya Zhou, Yuhang Wu, Zhiyue Wu +7
Symbolic Music, akin to language, can be encoded in discrete symbols. Recent research has extended the application of large language models (LLMs) such as GPT-4 and Llama2 to the s…
MMTrail: A Multimodal Trailer Video Dataset with Language and Music Descriptions
Xiaowei Chi, Yatian Wang, Aosong Cheng +16
Massive multi-modality datasets play a significant role in facilitating the success of large video-language models. However, current video-language datasets primarily provide text…
LLMs Meet Multimodal Generation and Editing: A Survey
Yingqing He, Zhaoyang Liu, Jingye Chen +13
With the recent advancement in large language models (LLMs), there is a growing interest in combining LLMs with multimodal learning. Previous surveys of multimodal large language m…
Multi-View Large Reconstruction Model via Geometry-Aware Positional Encoding and Attention
Mengfei Li, Xiaoxiao Long, Yixun Liang +6
Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits ine…
VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling
Zeyue Tian, Zhaoyang Liu, Ruibin Yuan +6
In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 360K video-music pairs, including various…
FastSAG: Towards Fast Non-Autoregressive Singing Accompaniment Generation
Jianyi Chen, Wei Xue, Xu Tan +3
Singing Accompaniment Generation (SAG), which generates instrumental music to accompany input vocals, is crucial to developing human-AI symbiotic art creation systems. The state-of…
ComposerX: Multi-Agent Symbolic Music Composition with LLMs
Qixin Deng, Qikai Yang, Ruibin Yuan +16
Music composition represents the creative side of humanity, and itself is a complex task that requires abilities to understand and generate information with long dependency and har…
FlashSpeech: Efficient Zero-Shot Speech Synthesis
Zhen Ye, Zeqian Ju, Haohe Liu +10
Recent progress in large-scale zero-shot speech synthesis has been significantly advanced by language models and diffusion models. However, the generation process of both methods i…
MuPT: A Generative Symbolic Music Pretrained Transformer
Xingwei Qu, Yuelin Bai, Yinghao Ma +25
In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music. While the prevalent use of MIDI in music modeling is well-established, our f…
RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation
Chi-Min Chan, Chunpu Xu, Ruibin Yuan +4
Large Language Models (LLMs) exhibit remarkable capabilities but are prone to generating inaccurate or hallucinatory responses. This limitation stems from their reliance on vast pr…
ChatMusician: Understanding and Generating Music Intrinsically with LLM
Ruibin Yuan, Hanfeng Lin, Yi Wang +32
While Large Language Models (LLMs) demonstrate impressive capabilities in text generation, we find that their ability has yet to be generalized to music, humanity's creative langua…
CoMoSVC: Consistency Model-based Singing Voice Conversion
Yiwen Lu, Zhen Ye, Wei Xue +3
The diffusion-based Singing Voice Conversion (SVC) methods have achieved remarkable performances, producing natural audios with high similarity to the target timbre. However, the i…