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Ziyao Guo

7 accepted papers

2025

OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation

CVPR 2025poster

Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a challenge, which requires integrated multimodal understanding and generation abilities. While the progress in unified mode…

2024

Identification of Analytic Nonlinear Dynamical Systems with Non-asymptotic Guarantees

NeurIPS 2024poster

This paper focuses on the system identification of an important class of nonlinear systems: nonlinear systems that are linearly parameterized, which enjoy wide applications in robotics and other mechanical systems. We consider two system identification methods: least-squares estimation (LSE), which…

2024

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching

ICML 2024poster

Graph condensation aims to reduce the size of a large-scale graph dataset by synthesizing a compact counterpart without sacrificing the performance of Graph Neural Networks (GNNs) trained on it, which has shed light on reducing the computational cost for training GNNs. Nevertheless, existing methods…

2024

Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality

NeurIPS 2024poster

Recent text-to-video (T2V) technology advancements, as demonstrated by models such as Gen2, Pika, and Sora, have significantly broadened its applicability and popularity. Despite these strides, evaluating these models poses substantial challenges. Primarily, due to the limitations inherent in auto…

2024

Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

ICLR 2024poster

The ultimate goal of Dataset Distillation is to synthesize a small synthetic dataset such that a model trained on this synthetic set will perform equally well as a model trained on the full, real dataset. Until now, no method of Dataset Distillation has reached this completely lossless goal, in part…

2022

ARCANE: An Efficient Architecture for Exact Machine Unlearning

IJCAI 2022poster

Recently users’ right-to-be-forgotten is stipulated by many laws and regulations. However, only removing the data from the dataset is not enough, as machine learning models would memorize the training data once the data is involved in model training, increasing the risk of exposing users’ privacy. T…

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