arXiv:2608. 08294v1 Announce Type: new Abstract: Knowledge distillation trains a smaller student to match the outputs of a larger teacher.
By Abhinand Balachandran, Praveen Prashant
arXiv:2609.22566v1 Announce Type: cross
Abstract: Knowledge distillation (KD) aims to compress high-performance teacher LLMs into lightweight students. However, distilled students often exhibit subst...
By Dileesha Kannangara, Sanghamitra Dutta
arXiv:2607. 07050v3 Announce Type: replace-cross Abstract: Top-K teacher logits make on-policy distillation tractable, but probability mass is not the same as decision support.
By Jiabin Shen, Guang Chen, Chengjun Mao
arXiv:2609.13199v1 Announce Type: new
Abstract: Knowledge distillation aims to improve the performance of lightweight student models by transferring knowledge from larger and more powerful teacher mo...
By Dawen Jiang, Zhishu Shen, Zeyu Liu, Tiehua Zhang
arXiv:2606. 25488v1 Announce Type: new Abstract: Knowledge Distillation (KD) is widely used to obtain compact models for efficient inference in resource-constrained environments.
By Yifan Wu, Yiqi Wang, Xichen Ye, Wenjing Yan, Xiaoqiang Li, Cheng Jin, Xiangyu Yue, Weizhong Zhang
arXiv:2609.39338v1 Announce Type: new
Abstract: Knowledge distillation transfers knowledge by encouraging a student to match a teacher's predicted class probabilities. These probabilities express not...
By Qianfeng Yuan, Wenbing Tao