Summary of Rethinking Optimization and Architecture For Tiny Language Models, by Yehui Tang et al.
Rethinking Optimization and Architecture for Tiny Language Modelsby Yehui Tang, Fangcheng Liu, Yunsheng Ni, Yuchuan…
Rethinking Optimization and Architecture for Tiny Language Modelsby Yehui Tang, Fangcheng Liu, Yunsheng Ni, Yuchuan…
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedbackby Gaurav Pandey, Yatin Nandwani,…
Diversity Measurement and Subset Selection for Instruction Tuning Datasetsby Peiqi Wang, Yikang Shen, Zhen Guo,…
Multi-modal Causal Structure Learning and Root Cause Analysisby Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng…
Selecting Large Language Model to Fine-tune via Rectified Scaling Lawby Haowei Lin, Baizhou Huang, Haotian…
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learningby Yiping…
HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QAby Xinyue Chen, Pengyu Gao, Jiangjiang Song,…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboardsby Norah Alzahrani, Hisham…
Continual Learning for Large Language Models: A Surveyby Tongtong Wu, Linhao Luo, Yuan-Fang Li, Shirui…
Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attackby Tiansheng Huang, Sihao Hu,…