4 papers
MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
MiniCPM Team, Wenhao An, Yingfa Chen +44
The evolution of large language models (LLMs) towards applications with ultra-long contexts faces challenges posed by the high computational and memory costs of the Transformer arc…
Unveiling and Bridging the Functional Perception Gap in MLLMs: Atomic Visual Alignment and Hierarchical Evaluation via PET-Bench
Zanting Ye, Xiaolong Niu, Xuanbin Wu +14
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in tasks such as abnormality detection and report generation for anatomical modalities, thei…
Lost in the Passage: Passage-level In-context Learning Does Not Necessarily Need a "Passage"
Hao Sun, Chenming Tang, Gengyang Li +1
By simply incorporating demonstrations into the context, in-context learning (ICL) enables large language models (LLMs) to yield awesome performance on many tasks. In this study, w…
Muyan-TTS: A Trainable Text-to-Speech Model Optimized for Podcast Scenarios with a $50K Budget
Xin Li, Kaikai Jia, Hao Sun +2
Recent advancements in text-to-speech (TTS) models have been driven by the integration of large language models (LLMs), enhancing semantic comprehension and improving speech natura…