18 citations · 20 across the 19 of their papers we have counts for
9 papers · 1 filter
Outlier-Aware Post-Training Quantization for Image Super-Resolution
Hailing Wang, jianglin Lu, Yitian Zhang +1
Quantization techniques, including quantization-aware training (QAT) and post-training quantization (PTQ), have become essential for inference acceleration of image super-resolutio…
SHIELD: Suppressing Hallucinations In LVLM Encoders via Bias and Vulnerability Defense
Yiyang Huang, Liang Shi, Yitian Zhang +2
Large Vision-Language Models (LVLMs) excel in diverse cross-modal tasks. However, object hallucination, where models produce plausible but inaccurate object descriptions, remains a…
MTS-DMAE: Dual-Masked Autoencoder for Unsupervised Multivariate Time Series Representation Learning
Yi Xu, Yitian Zhang, Yun Fu
Unsupervised multivariate time series (MTS) representation learning aims to extract compact and informative representations from raw sequences without relying on labels, enabling e…
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
Yitian Zhang, Liheng Ma, Antonios Valkanas +2
Koopman operator theory provides a framework for nonlinear dynamical system analysis and time-series forecasting by mapping dynamics to a space of real-valued measurement functions…
Trajectory Prediction Meets Large Language Models: A Survey
Yi Xu, Ruining Yang, Yitian Zhang +5
Recent advances in large language models (LLMs) have sparked growing interest in integrating language-driven techniques into trajectory prediction. By leveraging their semantic and…
REGEN: Learning Compact Video Embedding with (Re-)Generative Decoder
Yitian Zhang, Long Mai, Aniruddha Mahapatra +5
We present a novel perspective on learning video embedders for generative modeling: rather than requiring an exact reproduction of an input video, an effective embedder should focu…
GmNet: Revisiting Gating Mechanisms From A Frequency View
Yifan Wang, Xu Ma, Yitian Zhang +5
Gating mechanisms have emerged as an effective strategy integrated into model designs beyond recurrent neural networks for addressing long-range dependency problems. In a broad und…
Scale-Free Graph-Language Models
Jianglin Lu, Yixuan Liu, Yitian Zhang +1
Graph-language models (GLMs) have demonstrated great potential in graph-based semi-supervised learning. A typical GLM consists of two key stages: graph generation and text embeddin…
Progressive Growing of Video Tokenizers for Temporally Compact Latent Spaces
Aniruddha Mahapatra, Long Mai, David Bourgin +2
Video tokenizers are essential for latent video diffusion models, converting raw video data into spatiotemporally compressed latent spaces for efficient training. However, extendin…