activity
20182026
most citedOn Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection

336 citations · 539 across the 15 of their papers we have counts for

collaborators

17 papers

cs.AI2026

EmailBench: A Benchmark for Evaluating LLM Agents on Enterprise Email and Productivity Tasks

Mukul Singh, Mansi Uniyal, Devin Devlin +5

Enterprise email agents must combine information retrieval, structured state changes, temporal reasoning, and multi-step coordination. Recent agent benchmarks include productivity…

cs.CL2026

Users Mispredict Their Own Preferences for AI Writing Assistance

Vivian Lai, Zana Buçinca, Nil-Jana Akpinar +5

Proactive AI writing assistants need to predict when users want drafting help, yet we lack empirical understanding of what drives preferences. Through a factorial vignette study wi…

cs.HC2024

OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning

Jiaqi Ma, Vivian Lai, Yiming Zhang +5

Recently, there has been a surge of explainable AI (XAI) methods driven by the need for understanding machine learning model behaviors in high-stakes scenarios. However, properly e…

cs.IR2023★ 6 cited

Adversarial Collaborative Filtering for Free

Huiyuan Chen, Xiaoting Li, Vivian Lai +5

Collaborative Filtering (CF) has been successfully used to help users discover the items of interest. Nevertheless, existing CF methods suffer from noisy data issue, which negative…

cs.IR2023★ 5 cited

Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation

Vivian Lai, Huiyuan Chen, Chin-Chia Michael Yeh +3

Transformer and its variants are a powerful class of architectures for sequential recommendation, owing to their ability of capturing a user's dynamic interests from their past int…

cs.CL2023★ 1 cited

Evaluating Evaluation Metrics: A Framework for Analyzing NLG Evaluation Metrics using Measurement Theory

Ziang Xiao, Susu Zhang, Vivian Lai +1

We address a fundamental challenge in Natural Language Generation (NLG) model evaluation -- the design and evaluation of evaluation metrics. Recognizing the limitations of existing…