activity
20222024
most citedModel Agnostic Sample Reweighting for Out-of-Distribution Learning

10 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20241 cited

TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data

Jipeng Zhang, Yaxuan Qin, Renjie Pi +3

Instruction tuning has achieved unprecedented success in NLP, turning large language models into versatile chatbots. However, the increasing variety and volume of instruction datas…

cs.CV2024

Robust Fine-tuning for Pre-trained 3D Point Cloud Models

Zhibo Zhang, Ximing Yang, Weizhong Zhang +1

This paper presents a robust fine-tuning method designed for pre-trained 3D point cloud models, to enhance feature robustness in downstream fine-tuned models. We highlight the limi…

cs.LG2023

Test-Time Compensated Representation Learning for Extreme Traffic Forecasting

Zhiwei Zhang, Weizhong Zhang, Yaowei Huang +1

Traffic forecasting is a challenging task due to the complex spatio-temporal correlations among traffic series. In this paper, we identify an underexplored problem in multivariate…

cs.LG2023

Probabilistic Bilevel Coreset Selection

Xiao Zhou, Renjie Pi, Weizhong Zhang +2

The goal of coreset selection in supervised learning is to produce a weighted subset of data, so that training only on the subset achieves similar performance as training on the en…

cs.LG202310 cited

Model Agnostic Sample Reweighting for Out-of-Distribution Learning

Xiao Zhou, Yong Lin, Renjie Pi +4

Distributionally robust optimization (DRO) and invariant risk minimization (IRM) are two popular methods proposed to improve out-of-distribution (OOD) generalization performance of…

cs.DS2022

Approximation algorithms for Steiner Tree Augmentation Problems

R. Ravi, Weizhong Zhang, Michael Zlatin

In the Steiner Tree Augmentation Problem (STAP), we are given a graph , a set of terminals , and a Steiner tree spanning . The edges $L := E \setmi…