11 papers
HeartMuLa: A Family of Open Sourced Music Foundation Models
Dongchao Yang, Yuxin Xie, Yuguo Yin +26
We present a family of open-source Music Foundation Models designed to advance large-scale music understanding and generation across diverse tasks and modalities. Our framework con…
Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification
Wujian Peng, Lingchen Meng, Yuxuan Cai +7
Unified Multimodal Modeling aims to integrate visual understanding and generation within a single system. However, existing approaches typically rely on two disparate visual tokeni…
Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments
Qiuyue Wang, Mingsheng Li, Jian Guan +37
Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented capabilities and limited generali…
ASK: Adaptive Self-improving Knowledge Framework for Audio Text Retrieval
Siyuan Fu, Xuchen Guo, Mingjun Liu +7
The dominant paradigm for Audio-Text Retrieval (ATR) relies on dual-encoder architectures optimized via mini-batch contrastive learning. However, restricting optimization to local…
SupCLAP: Controlling Optimization Trajectory Drift in Audio-Text Contrastive Learning with Support Vector Regularization
Jiehui Luo, Yuguo Yin, Yuxin Xie +6
Contrastive language-audio pretraining, which aims to unify multimodal representations in a shared embedding space, serves as a cornerstone for building a wide range of application…
Not All Tokens and Heads Are Equally Important: Dual-Level Attention Intervention for Hallucination Mitigation
Lexiang Tang, Xianwei Zhuang, Bang Yang +5
Large vision-language models (LVLMs) have demonstrated impressive capabilities across diverse multimodal tasks, yet they remain highly susceptible to visual hallucinations (VH), of…