Summary of Eagle: Speculative Sampling Requires Rethinking Feature Uncertainty, by Yuhui Li et al.
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertaintyby Yuhui Li, Fangyun Wei, Chao Zhang, Hongyang ZhangFirst…
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertaintyby Yuhui Li, Fangyun Wei, Chao Zhang, Hongyang ZhangFirst…
Adaptive Point Transformerby Alessandro Baiocchi, Indro Spinelli, Alessandro Nicolosi, Simone ScardapaneFirst submitted to arxiv on:…
MoE-Infinity: Efficient MoE Inference on Personal Machines with Sparsity-Aware Expert Cacheby Leyang Xue, Yao Fu,…
Instruction Fine-Tuning: Does Prompt Loss Matter?by Mathew Huerta-Enochian, Seung Yong KoFirst submitted to arxiv on:…
SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detectionby Ke Ye, Heinrich Jiang,…
Topic Modelling: Going Beyond Token Outputsby Lowri Williams, Eirini Anthi, Laura Arman, Pete BurnapFirst submitted…
Universal Neurons in GPT2 Language Modelsby Wes Gurnee, Theo Horsley, Zifan Carl Guo, Tara Rezaei…
Anchor function: a type of benchmark functions for studying language modelsby Zhongwang Zhang, Zhiwei Wang,…
Robust Semi-Supervised Learning for Self-learning Open-World Classesby Wenjuan Xi, Xin Song, Weili Guo, Yang YangFirst…
An Exploratory Assessment of LLM’s Potential Toward Flight Trajectory Reconstruction Analysisby Qilei Zhang, John H.…