Summary of Reverse-engineering the Reader, by Samuel Kiegeland et al.
Reverse-Engineering the Readerby Samuel Kiegeland, Ethan Gotlieb Wilcox, Afra Amini, David Robert Reich, Ryan CotterellFirst…
Summary of End-to-end Planner Training For Language Modeling, by Nathan Cornille et al.
End-to-end Planner Training for Language Modelingby Nathan Cornille, Florian Mai, Jingyuan Sun, Marie-Francine MoensFirst submitted…
Summary of Daq: Density-aware Post-training Weight-only Quantization For Llms, by Yingsong Luo et al.
DAQ: Density-Aware Post-Training Weight-Only Quantization For LLMsby Yingsong Luo, Ling ChenFirst submitted to arxiv on:…
Summary of Alphapruning: Using Heavy-tailed Self Regularization Theory For Improved Layer-wise Pruning Of Large Language Models, by Haiquan Lu et al.
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Modelsby Haiquan…
Summary of Continuous Approximations For Improving Quantization Aware Training Of Llms, by He Li et al.
Continuous Approximations for Improving Quantization Aware Training of LLMsby He Li, Jianhang Hong, Yuanzhuo Wu,…
Summary of Relu’s Revival: on the Entropic Overload in Normalization-free Large Language Models, by Nandan Kumar Jha and Brandon Reagen
ReLU’s Revival: On the Entropic Overload in Normalization-Free Large Language Modelsby Nandan Kumar Jha, Brandon…
Summary of Crossquant: a Post-training Quantization Method with Smaller Quantization Kernel For Precise Large Language Model Compression, by Wenyuan Liu et al.
CrossQuant: A Post-Training Quantization Method with Smaller Quantization Kernel for Precise Large Language Model Compressionby…
Summary of Think While You Generate: Discrete Diffusion with Planned Denoising, by Sulin Liu et al.
Think While You Generate: Discrete Diffusion with Planned Denoisingby Sulin Liu, Juno Nam, Andrew Campbell,…
Summary of Qera: An Analytical Framework For Quantization Error Reconstruction, by Cheng Zhang et al.
QERA: an Analytical Framework for Quantization Error Reconstructionby Cheng Zhang, Jeffrey T. H. Wong, Can…
Summary of Language Model-driven Data Pruning Enables Efficient Active Learning, by Abdul Hameed Azeemi et al.
Language Model-Driven Data Pruning Enables Efficient Active Learningby Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha…