Summary of Inducing Group Fairness in Prompt-based Language Model Decisions, by James Atwood et al.
Inducing Group Fairness in Prompt-Based Language Model Decisionsby James Atwood, Nino Scherrer, Preethi Lahoti, Ananth…
Summary of Autodetect: Towards a Unified Framework For Automated Weakness Detection in Large Language Models, by Jiale Cheng et al.
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Modelsby Jiale Cheng,…
Summary of Gc4nc: a Benchmark Framework For Graph Condensation on Node Classification with New Insights, by Shengbo Gong et al.
GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insightsby Shengbo Gong,…
Summary of Anomaly Detection Of Tabular Data Using Llms, by Aodong Li et al.
Anomaly Detection of Tabular Data Using LLMsby Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft,…
Summary of Multimodal Graph Benchmark, by Jing Zhu et al.
Multimodal Graph Benchmarkby Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah,…
Summary of Does Cross-cultural Alignment Change the Commonsense Morality Of Language Models?, by Yuu Jinnai
Does Cross-Cultural Alignment Change the Commonsense Morality of Language Models?by Yuu JinnaiFirst submitted to arxiv…
Summary of Annotatedtables: a Large Tabular Dataset with Language Model Annotations, by Yaojie Hu et al.
AnnotatedTables: A Large Tabular Dataset with Language Model Annotationsby Yaojie Hu, Ilias Fountalis, Jin Tian,…
Summary of Metrik: Measurement-efficient Randomized Controlled Trials Using Transformers with Input Masking, by Sayeri Lala (1) and Niraj K. Jha (1) ((1) Princeton University et al.
METRIK: Measurement-Efficient Randomized Controlled Trials using Transformers with Input Maskingby Sayeri Lala, Niraj K. JhaFirst…
Summary of Compact Model Parameter Extraction Via Derivative-free Optimization, by Rafael Perez Martinez et al.
Compact Model Parameter Extraction via Derivative-Free Optimizationby Rafael Perez Martinez, Masaya Iwamoto, Kelly Woo, Zhengliang…
Summary of Theory on Mixture-of-experts in Continual Learning, by Hongbo Li et al.
Theory on Mixture-of-Experts in Continual Learningby Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness…