5 papers
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…
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…
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…
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…