Search Results for author:
Found 9 papers, 3 papers with code
EasyTPP: Towards Open Benchmarking Temporal Point Processes
In this paper, we present EasyTPP, the first central repository of research assets (e. g., data, models, evaluation programs, documentations) in the area of event sequence modeling.
Temporal Convolutional Attention-based Network For Sequence Modeling
So we propose an exploratory architecture referred to Temporal Convolutional Attention-based Network (TCAN) which combines temporal convolutional network and attention mechanism.
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine
We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain.
Learning Large-scale Universal User Representation with Sparse Mixture of Experts
However, unlike natural language processing (NLP) tasks, the parameters of user behaviour model come mostly from user embedding layer, which makes most existing works fail in training a universal user embedding of large scale.
A Graph Regularized Point Process Model For Event Propagation Sequence
Point process is the dominant paradigm for modeling event sequences occurring at irregular intervals.
Continual Learning in Predictive Autoscaling
In order to surmount this challenge and effectively integrate new sample distribution, we propose a density-based sample selection strategy that utilizes kernel density estimation to calculate sample density as a reference to compute sample weight, and employs weight sampling to construct a new memory set.
Leveraging Large Language Models for Pre-trained Recommender Systems
In this paper, we propose RecSysLLM, a novel pre-trained recommendation model based on LLMs.
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
In this paper, we propose a novel approach that leverages large language models (LLMs) to construct personalized reasoning graphs.
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference
Asynchronous time series, also known as temporal event sequences, are the basis of many applications throughout different industries.
