6 citations · 11 across the 3 of their papers we have counts for
5 papers
Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting
Wenjie Ou, Zhishuo Zhao, Cheng Chen +2
Time series forecasting is critical across multiple domains, where time series data exhibit both local patterns and global dependencies. While Transformer-based methods effectively…
DR-RAG: Applying Dynamic Document Relevance to Retrieval-Augmented Generation for Question-Answering
Zijian Hei, Weiling Liu, Wenjie Ou +5
Retrieval-Augmented Generation (RAG) has recently demonstrated the performance of Large Language Models (LLMs) in the knowledge-intensive tasks such as Question-Answering (QA). RAG…
Effective Unsupervised Constrained Text Generation based on Perturbed Masking
Yingwen Fu, Wenjie Ou, Zhou Yu +1
Unsupervised constrained text generation aims to generate text under a given set of constraints without any supervised data. Current state-of-the-art methods stochastically sample…
WinNet: Make Only One Convolutional Layer Effective for Time Series Forecasting
Wenjie Ou, Zhishuo Zhao, Dongyue Guo +2
Deep learning models have recently achieved significant performance improvements in time series forecasting. We present a highly accurate and simply structured CNN-based model with…
A Clarifying Question Selection System from NTES_ALONG in Convai3 Challenge
Wenjie Ou, Yue Lin
This paper presents the participation of NetEase Game AI Lab team for the ClariQ challenge at Search-oriented Conversational AI (SCAI) EMNLP workshop in 2020. The challenge asks fo…