Summary of Map-neo: Highly Capable and Transparent Bilingual Large Language Model Series, by Ge Zhang et al.
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Seriesby Ge Zhang, Scott Qu, Jiaheng…
Summary of Compressing Large Language Models Using Low Rank and Low Precision Decomposition, by Rajarshi Saha et al.
Compressing Large Language Models using Low Rank and Low Precision Decompositionby Rajarshi Saha, Naomi Sagan,…
Summary of Language Generation with Strictly Proper Scoring Rules, by Chenze Shao et al.
Language Generation with Strictly Proper Scoring Rulesby Chenze Shao, Fandong Meng, Yijin Liu, Jie ZhouFirst…
Summary of Understanding Intrinsic Socioeconomic Biases in Large Language Models, by Mina Arzaghi et al.
Understanding Intrinsic Socioeconomic Biases in Large Language Modelsby Mina Arzaghi, Florian Carichon, Golnoosh FarnadiFirst submitted…
Summary of On the Origin Of Llamas: Model Tree Heritage Recovery, by Eliahu Horwitz et al.
On the Origin of Llamas: Model Tree Heritage Recoveryby Eliahu Horwitz, Asaf Shul, Yedid HoshenFirst…
Summary of 2bp: 2-stage Backpropagation, by Christopher Rae et al.
2BP: 2-Stage Backpropagationby Christopher Rae, Joseph K. L. Lee, James RichingsFirst submitted to arxiv on:…
Summary of Online Merging Optimizers For Boosting Rewards and Mitigating Tax in Alignment, by Keming Lu et al.
Online Merging Optimizers for Boosting Rewards and Mitigating Tax in Alignmentby Keming Lu, Bowen Yu,…
Summary of On Fairness Of Low-rank Adaptation Of Large Models, by Zhoujie Ding and Ken Ziyu Liu and Pura Peetathawatchai and Berivan Isik and Sanmi Koyejo
On Fairness of Low-Rank Adaptation of Large Modelsby Zhoujie Ding, Ken Ziyu Liu, Pura Peetathawatchai,…
Summary of Claq: Pushing the Limits Of Low-bit Post-training Quantization For Llms, by Haoyu Wang et al.
CLAQ: Pushing the Limits of Low-Bit Post-Training Quantization for LLMsby Haoyu Wang, Bei Liu, Hang…
Summary of On the Algorithmic Bias Of Aligning Large Language Models with Rlhf: Preference Collapse and Matching Regularization, by Jiancong Xiao et al.
On the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching…