10 citations · 42 across the 19 of their papers we have counts for
12 papers · 1 filter
NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning
Zheyuan Zhang, Yiyang Li, Nhi Ha Lan Le +9
Diet plays a critical role in human health, yet tailoring dietary reasoning to individual health conditions remains a major challenge. Nutrition Question Answering (QA) has emerged…
Class-Aware Contrastive Optimization for Imbalanced Text Classification
Grigorii Khvatskii, Nuno Moniz, Khoa Doan +1
The unique characteristics of text data make classification tasks a complex problem. Advances in unsupervised and semi-supervised learning and autoencoder architectures addressed s…
Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Jiayi Ye, Yanbo Wang, Yue Huang +9
LLM-as-a-Judge has been widely utilized as an evaluation method in various benchmarks and served as supervised rewards in model training. However, despite their excellence in many…
LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs
Yujun Zhou, Jingdong Yang, Yue Huang +12
Artificial Intelligence (AI) is revolutionizing scientific research, yet its growing integration into laboratory environments presents critical safety challenges. Large language mo…
BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks
Anna Sokol, Elizabeth Daly, Michael Hind +4
Large language models (LLMs) are powerful tools capable of handling diverse tasks. Comparing and selecting appropriate LLMs for specific tasks requires systematic evaluation method…
Empowering Open Data Sharing for Social Good: A Privacy-Aware Approach
Tânia Carvalho, Luís Antunes, Cristina Costa +1
The Covid-19 pandemic has affected the world at multiple levels. Data sharing was pivotal for advancing research to understand the underlying causes and implement effective contain…
Automated Privacy-Preserving Techniques via Meta-Learning
Tânia Carvalho, Nuno Moniz, Luís Antunes
Sharing private data for learning tasks is pivotal for transparent and secure machine learning applications. Many privacy-preserving techniques have been proposed for this task aim…
Synthetic Data Outliers: Navigating Identity Disclosure
Carolina Trindade, Luís Antunes, Tânia Carvalho +1
Multiple synthetic data generation models have emerged, among which deep learning models have become the vanguard due to their ability to capture the underlying characteristics of…
AnyLoss: Transforming Classification Metrics into Loss Functions
Doheon Han, Nuno Moniz, Nitesh V Chawla
Many evaluation metrics can be used to assess the performance of models in binary classification tasks. However, most of them are derived from a confusion matrix in a non-different…
Fast Explanations via Policy Gradient-Optimized Explainer
Deng Pan, Nuno Moniz, Nitesh Chawla
The challenge of delivering efficient explanations is a critical barrier that prevents the adoption of model explanations in real-world applications. Existing approaches often depe…
Conformalized Selective Regression
Anna Sokol, Nuno Moniz, Nitesh Chawla
Should prediction models always deliver a prediction? In the pursuit of maximum predictive performance, critical considerations of reliability and fairness are often overshadowed,…
Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective
Yihong Ma, Xiaobao Huang, Bozhao Nan +4
The yield of a chemical reaction quantifies the percentage of the target product formed in relation to the reactants consumed during the chemical reaction. Accurate yield predictio…