10 papers
TLRD: Teaching LLMs to Reason over Tabular Data with Tri-Level Rationale Distillation
Tianyuan Liang, Xuwei Tan, Lei Shi +6
Tabular data is a primary medium for storing real-world information, driving many industrial applications of machine learning. Traditional predictors achieve strong predictive perf…
Benchmarking Bias Mitigation Toward Fairness Without Harm from Vision to LVLMs
Xuwei Tan, Ziyu Hu, Xueru Zhang
Machine learning models trained on real-world data often inherit and amplify biases against certain social groups, raising urgent concerns about their deployment at scale. While nu…
DABench-LLM: Standardized and In-Depth Benchmarking of Post-Moore Dataflow AI Accelerators for LLMs
Ziyu Hu, Zhiqing Zhong, Weijian Zheng +6
The exponential growth of large language models has outpaced the capabilities of traditional CPU and GPU architectures due to the slowdown of Moore's Law. Dataflow AI accelerators…
Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection
Xuwei Tan, Yao Ma, Xueru Zhang
Detecting fraud in financial transactions typically relies on tabular models that demand heavy feature engineering to handle high-dimensional data and offer limited interpretabilit…
Achieving Fairness Without Harm via Selective Demographic Experts
Xuwei Tan, Yuanlong Wang, Thai-Hoang Pham +2
As machine learning systems become increasingly integrated into human-centered domains such as healthcare, ensuring fairness while maintaining high predictive performance is critic…
Deep learning for flash drought forecasting and interpretation
Qian Zhao, Xuwei Tan, Xueru Zhang +2
Flash droughts are increasingly occurring worldwide due to climate change, causing widespread socioeconomic and agricultural losses. However, timely and accurate flash drought fore…
DroughtSet: Understanding Drought Through Spatial-Temporal Learning
Xuwei Tan, Qian Zhao, Yanlan Liu +1
Drought is one of the most destructive and expensive natural disasters, severely impacting natural resources and risks by depleting water resources and diminishing agricultural yie…
Lookahead Counterfactual Fairness
Zhiqun Zuo, Tian Xie, Xuwei Tan +2
As machine learning (ML) algorithms are used in applications that involve humans, concerns have arisen that these algorithms may be biased against certain social groups. \textit{Co…
ProFL: Performative Robust Optimal Federated Learning
Xue Zheng, Tian Xie, Xuwei Tan +2
Performative prediction is a framework that captures distribution shifts that occur during the training of machine learning models due to their deployment. As the trained model is…
Algorithmic Decision-Making under Agents with Persistent Improvement
Tian Xie, Xuwei Tan, Xueru Zhang
This paper studies algorithmic decision-making under human's strategic behavior, where a decision maker uses an algorithm to make decisions about human agents, and the latter with…