Yunshui Li

Scaling Law for Quantization-Aware Training

HSA: Head-wise Sparse Attention for Efficient and Accurate Long-context Inference

INT v.s. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats

DEEM: Diffusion models serve as the eyes of large language models for image perception

Model Merging in Pre-training of Large Language Models

MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct

Selecting Influential Samples for Long Context Alignment via Homologous Models’ Guidance and Contextual Awareness Measurement