5 papers
Long-range Modeling and Processing of Multimodal Event Sequences
Jichu Li, Yilun Zhong, Zhiting Li +2
Temporal point processes (TPPs) have emerged as powerful tools for modeling asynchronous event sequences. While recent advances have extended TPPs to handle textual information, ex…
Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
Yixuan Zhang, Jinhao Sheng, Wenxin Zhang +2
Although artificial neural networks are often described as brain-inspired, their representations typically rely on continuous activations, such as the continuous latent variables i…
TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding
Shukai Gong, Yiyang Fu, Fengyuan Ran +2
We propose TPP-SD, a novel approach that accelerates Transformer temporal point process (TPP) sampling by adapting speculative decoding (SD) techniques from language models. By ide…
DanmakuTPPBench: A Multi-modal Benchmark for Temporal Point Process Modeling and Understanding
Yue Jiang, Jichu Li, Yang Liu +3
We introduce DanmakuTPPBench, a comprehensive benchmark designed to advance multi-modal Temporal Point Process (TPP) modeling in the era of Large Language Models (LLMs). While TPPs…
Byte-token Enhanced Language Models for Temporal Point Processes Analysis
Quyu Kong, Yixuan Zhang, Yang Liu +3
Temporal Point Processes (TPPs) have been widely used for modeling event sequences on the Web, such as user reviews, social media posts, and online transactions. However, tradition…