8 citations · 8 across the 7 of their papers we have counts for
10 papers
RAIGen: Rare Attribute Identification in Text-to-Image Generative Models
Silpa Vadakkeeveetil Sreelatha, Dan Wang, Serge Belongie +2
Text-to-image diffusion models achieve impressive generation quality but inherit and amplify training-data biases, skewing coverage of semantic attributes. Prior work addresses thi…
Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Wenxuan Wang, Kai Wu, Yujian Betterest Li +2
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as training data scarcity and imbalance continue to hinder their dev…
Fine Tuning Methods for Low-resource Languages
Tim Bakkenes, Daniel Wang, Anton Johansson
The rise of Large Language Models has not been inclusive of all cultures. The models are mostly trained on English texts and culture which makes them underperform in other language…
Driving Accurate Allergen Prediction with Protein Language Models and Generalization-Focused Evaluation
Brian Shing-Hei Wong, Joshua Mincheol Kim, Sin-Hang Fung +11
Allergens, typically proteins capable of triggering adverse immune responses, represent a significant public health challenge. To accurately identify allergen proteins, we introduc…
Measuring Stereotype and Deviation Biases in Large Language Models
Daniel Wang, Eli Brignac, Minjia Mao +1
Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study, we investigate two types of bia…
KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answering
Zhongze Luo, Weixuan Wan, Tianya Zhang +2
The rapid evolution of communication technologies has led to an explosion of standards, rendering traditional expert-dependent consultation methods inefficient and slow. To address…
Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
Wenxuan Wang, Kai Wu, Yujian Betterest Li +3
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as data scarcity and data imbalance continue to hinder their develop…
Comparing Fairness of Generative Mobility Models
Daniel Wang, Jack McFarland, Afra Mashhadi +1
This work examines the fairness of generative mobility models, addressing the often overlooked dimension of equity in model performance across geographic regions. Predictive models…
A Systematic Review on Prompt Engineering in Large Language Models for K-12 STEM Education
Eason Chen, Danyang Wang, Luyi Xu +3
Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising result…
Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data
Danyang Wang, Chengchun Shi, Shikai Luo +1
In real-world scenarios, datasets collected from randomized experiments are often constrained by size, due to limitations in time and budget. As a result, leveraging large observat…