13 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…
GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
Yan Jiang, Ruihong Qiu, Zi Huang
Graph prompt tuning has shown great potential in graph learning by introducing trainable prompts to enhance the model performance in conventional single-domain scenarios. Recent re…
What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition
Danny Wang, Ruihong Qiu, Zi Huang
Graph neural networks are widely used for node classification, but they remain vulnerable to out-of-distribution (OOD) shifts in node features and graph structure. Prior work estab…
Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models
Yan Jiang, Ruihong Qiu, Zi Huang
Recently, reinforcement learning (RL) has been widely applied during post-training for diffusion large language models (dLLMs) to enhance reasoning with block-wise semi-autoregress…
Skill-R1: Agent Skill Evolution via Reinforcement Learning
Yash Vishe, Rohan Surana, Xunyi Jiang +8
Agentic large language models often rely on skills, reusable natural language procedures that guide planning, action, and tool use. In practice, skills are typically improved throu…
Skill-CMIB: Multimodal Agent Skill for Consistent Action via Conditional Multimodal Information Bottleneck
Zihan Huang, Junda Wu, Tong Yu +6
While LLM-based agents excel at planning and executing long action sequences, their execution often remains inconsistent across trials, limiting reliability. Consolidating agent co…