22 citations · 57 across the 9 of their papers we have counts for
11 papers
SEAL : Interactive Tool for Systematic Error Analysis and Labeling
Nazneen Rajani, Weixin Liang, Lingjiao Chen +2
With the advent of Transformers, large language models (LLMs) have saturated well-known NLP benchmarks and leaderboards with high aggregate performance. However, many times these m…
Data Budgeting for Machine Learning
Xinyi Zhao, Weixin Liang, James Zou
Data is the fuel powering AI and creates tremendous value for many domains. However, collecting datasets for AI is a time-consuming, expensive, and complicated endeavor. For practi…
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts
Weixin Liang, James Zou
Understanding the performance of machine learning models across diverse data distributions is critically important for reliable applications. Motivated by this, there is a growing…
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
Weixin Liang, Kai-Hui Liang, Zhou Yu
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience. User engagement is one of the most important metrics for evaluating…
GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering
Weixin Liang, Yanhao Jiang, Zixuan Liu
Images are more than a collection of objects or attributes -- they represent a web of relationships among interconnected objects. Scene Graph has emerged as a new modality for a st…
LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering
Weixin Liang, Feiyang Niu, Aishwarya Reganti +2
The predominant approach to visual question answering (VQA) relies on encoding the image and question with a "black-box" neural encoder and decoding a single token as the answer li…