15 papers
MuseCritic: Learning Multi-Aspect Song Rewards through Natural-Language Aesthetic Critiques
Jiabao Zhuang, Changhao Jiang, Hanchen Wang +11
Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards increasingly important for aligni…
CL-bench Life: Can Language Models Learn from Real-Life Context?
Shihan Dou, Yujiong Shen, Chenhao Huang +35
Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for models. As these systems move be…
SpeechRole: A Large-Scale Dataset and Benchmark for Evaluating Speech Role-Playing Agents
Changhao Jiang, Jiajun Sun, Yifei Cao +15
Speech is essential for realistic role-playing, yet existing work on role-playing agents largely centers on text, leaving Speech Role-Playing Agents (SRPAs) underexplored and witho…
Why Reinforcement Fine-Tuning Enables MLLMs Preserve Prior Knowledge Better: A Data Perspective
Zhihao Zhang, Qiaole Dong, Qi Zhang +12
Post-training algorithms such as Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT) are widely used to adapt (multimodal) large language models to downstream tasks. W…
MHA2MLA-VLM: Enabling DeepSeek's Economical Multi-Head Latent Attention across Vision-Language Models
Xiaoran Fan, Zhichao Sun, Tao Ji +2
As vision-language models (VLMs) tackle increasingly complex and multimodal tasks, the rapid growth of Key-Value (KV) cache imposes significant memory and computational bottlenecks…
What Makes a Good Speech Tokenizer for LLM-Centric Speech Generation? A Systematic Study
Xiaoran Fan, Zhichao Sun, Yangfan Gao +19
Speech-language models (SLMs) offer a promising path toward unifying speech and text understanding and generation. However, challenges remain in achieving effective cross-modal ali…