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cs.LG2026
FastMix: Fast Data Mixture Optimization via Gradient Descent
Haoru Tan, Sitong Wu, Yanfeng Chen +5
While large and diverse datasets have driven recent advances in large models, identifying the optimal data mixture for pre-training and post-training remains a significant open pro…
cs.CV2026
MHSA: A Lightweight Framework for Mitigating Hallucinations via Steered Attention in LVLMs
Wei Ding, Yilin Li, Yudong Zhang +4
Large vision-language models (LVLMs) have achieved remarkable performance across diverse multimodal tasks, yet they continue to suffer from hallucinations, generating content that…
cs.CL2026
Self-Distillation for Multi-Token Prediction
Guoliang Zhao, Ruobing Xie, An Wang +3
As Large Language Models (LLMs) scale up, inference efficiency becomes a critical bottleneck. Multi-Token Prediction (MTP) could accelerate LLM inference by predicting multiple fut…