14 citations · 18 across the 4 of their papers we have counts for
5 papers
OhmicFlow: Forecasting transit passenger flow under extreme weather disruptions via Ohm's law
Tianhao Li, Xintian Liu, Zhan Zhao
As climate change intensifies, extreme weather events (EWEs) increasingly disrupt the supply-demand balance of mass transit systems. Accurate and reliable prediction of origin-dest…
CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models
Tianhao Li, Sandesh Shetty, Advaith Kamath +4
Large pre-trained language models (LLMs) have been shown to have significant potential in few-shot learning across various fields, even with minimal training data. However, their a…
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search
Yiming Qiu, Chenyu Zhao, Han Zhang +7
BERT-style models pre-trained on the general corpus (e.g., Wikipedia) and fine-tuned on specific task corpus, have recently emerged as breakthrough techniques in many NLP tasks: qu…
Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding
Zhenzhi Wang, Limin Wang, Tao Wu +2
Temporal grounding aims to localize a video moment which is semantically aligned with a given natural language query. Existing methods typically apply a detection or regression pip…
A parallel-network continuous quantitative trading model with GARCH and PPO
Zhishun Wang, Wei Lu, Kaixin Zhang +2
It is a difficult task for both professional investors and individual traders continuously making profit in stock market. With the development of computer science and deep reinforc…