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08/20/2023
Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation
Transformer and its variants are a powerful class of architectures for s...
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08/20/2023
Adversarial Collaborative Filtering for Free
Collaborative Filtering (CF) has been successfully used to help users di...
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07/18/2023
Sharpness-Aware Graph Collaborative Filtering
Graph Neural Networks (GNNs) have achieved impressive performance in col...
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05/24/2023
Evaluating NLG Evaluation Metrics: A Measurement Theory Perspective
We address the fundamental challenge in Natural Language Generation (NLG...
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01/23/2023
Selective Explanations: Leveraging Human Input to Align Explainable AI
While a vast collection of explainable AI (XAI) algorithms have been dev...
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06/13/2022
An Exploration of Post-Editing Effectiveness in Text Summarization
Automatic summarization methods are efficient but can suffer from low qu...
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04/25/2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation
Despite impressive performance in many benchmark datasets, AI models can...
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12/21/2021
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies
As AI systems demonstrate increasingly strong predictive performance, th...
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04/29/2021
Using Transformers to Provide Teachers with Personalized Feedback on their Classroom Discourse: The TalkMoves Application
TalkMoves is an innovative application designed to support K-12 mathemat...
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01/13/2021
Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making
Although AI holds promise for improving human decision making in societa...
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03/16/2020
Harnessing Explanations to Bridge AI and Humans
Machine learning models are increasingly integrated into societally crit...
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01/14/2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans
To support human decision making with machine learning models, we often ...
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10/18/2019
Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification
Feature importance is commonly used to explain machine predictions. Whil...
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11/19/2018