7 papers
Counting Hallucinations in Diffusion Models
Shuai Fu, Jian Zhou, Qi Chen +7
Diffusion probabilistic models (DPMs) have demonstrated remarkable progress in generative tasks, such as image and video synthesis. However, they still often produce hallucinated s…
Disentangling Regional Primitives for Image Generation
Zhengting Chen, Lei Cheng, Lianghui Ding +2
This paper explains a neural network for image generation from a new perspective, i.e., explaining representation structures for image generation. We propose a set of desirable pro…
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…
Quantifying In-Context Reasoning Effects and Memorization Effects in LLMs
Siyu Lou, Yuntian Chen, Xiaodan Liang +2
In this study, we propose an axiomatic system to define and quantify the precise memorization and in-context reasoning effects used by the large language model (LLM) for language g…