3 papers
cs.CV2026
Once-For-All: A Train-Once and Select-Anytime Framework for Multimodal Instruction Tuning
Mingkang Dong, Hongyi Cai, Xiwen Lei +3
Multimodal instruction tuning is the de facto recipe for adapting vision language models (VLMs), yet instruction data are highly redundant, making data selection critical for train…
cs.LG2025
MixKVQ: Query-Aware Mixed-Precision KV Cache Quantization for Long-Context Reasoning
Tao Zhang, Ziqian Zeng, Hao Peng +2
Long Chain-of-Thought (CoT) reasoning has significantly advanced the capabilities of Large Language Models (LLMs), but this progress is accompanied by substantial memory and latenc…
cs.CL2024
GenderAlign: An Alignment Dataset for Mitigating Gender Bias in Large Language Models
Tao Zhang, Ziqian Zeng, Yuxiang Xiao +4
Large Language Models (LLMs) are prone to generating content that exhibits gender biases, raising significant ethical concerns. Alignment, the process of fine-tuning LLMs to better…