1 citations · 2 across the 7 of their papers we have counts for
7 papers
How Does Parameter Pruning Reshape DNN Representations? An Interaction-Driven Exploration
Fangbo Li, Junpeng Zhang, Qihan Ren +1
This study focuses on the scientific problem of understanding internal factors that govern the diverse performance degradation of deep neural networks (DNNs) when different paramet…
Reconciling Contradictory Views on the Effectiveness of SFT in LLMs: An Interaction Perspective
Junpeng Zhang, Lei Cheng, Guoxi Zhang +3
This paper explores a scientific question in supervised fine-tuning (SFT): why SFT is broadly effective for small-scale deep neural networks, yet can produce inconsistent or even d…
Technical Report: Quantifying and Analyzing the Generalization Power of a DNN
Yuxuan He, Junpeng Zhang, Lei Cheng +2
This paper proposes a new perspective for analyzing the generalization power of deep neural networks (DNNs), i.e., directly disentangling and analyzing the dynamics of generalizabl…
Revisiting Generalization Power of a DNN in Terms of Symbolic Interactions
Lei Cheng, Junpeng Zhang, Qihan Ren +1
This paper aims to analyze the generalization power of deep neural networks (DNNs) from the perspective of interactions. Unlike previous analysis of a DNN's generalization power in…
Randomness of Low-Layer Parameters Determines Confusing Samples in Terms of Interaction Representations of a DNN
Junpeng Zhang, Lei Cheng, Qing Li +2
In this paper, we find that the complexity of interactions encoded by a deep neural network (DNN) can explain its generalization power. We also discover that the confusing samples…
Towards the Dynamics of a DNN Learning Symbolic Interactions
Qihan Ren, Junpeng Zhang, Yang Xu +3
This study proves the two-phase dynamics of a deep neural network (DNN) learning interactions. Despite the long disappointing view of the faithfulness of post-hoc explanation of a…
Two-Phase Dynamics of Interactions Explains the Starting Point of a DNN Learning Over-Fitted Features
Junpeng Zhang, Qing Li, Liang Lin +1
This paper investigates the dynamics of a deep neural network (DNN) learning interactions. Previous studies have discovered and mathematically proven that given each input sample,…