Summary of Linking Model Intervention to Causal Interpretation in Model Explanation, by Debo Cheng et al.
Linking Model Intervention to Causal Interpretation in Model Explanationby Debo Cheng, Ziqi Xu, Jiuyong Li,…
Summary of Understanding and Alleviating Memory Consumption in Rlhf For Llms, by Jin Zhou et al.
Understanding and Alleviating Memory Consumption in RLHF for LLMsby Jin Zhou, Hanmei Yang, Steven, Tang,…
Summary of Accounting For Missing Covariates in Heterogeneous Treatment Estimation, by Khurram Yamin et al.
Accounting for Missing Covariates in Heterogeneous Treatment Estimationby Khurram Yamin, Vibhhu Sharma, Ed Kennedy, Bryan…
Summary of Accelerated Sub-image Search For Variable-size Patches Identification Based on Virtual Time Series Transformation and Segmentation, by Mogens Plessen
Accelerated Sub-Image Search For Variable-Size Patches Identification Based On Virtual Time Series Transformation And Segmentationby…
Summary of Power Plays: Unleashing Machine Learning Magic in Smart Grids, by Abdur Rashid et al.
Power Plays: Unleashing Machine Learning Magic in Smart Gridsby Abdur Rashid, Parag Biswas, abdullah al…
Summary of Data Augmentation Via Diffusion Model to Enhance Ai Fairness, by Christina Hastings Blow et al.
Data Augmentation via Diffusion Model to Enhance AI Fairnessby Christina Hastings Blow, Lijun Qian, Camille…
Summary of Generative Models, Humans, Predictive Models: Who Is Worse at High-stakes Decision Making?, by Keri Mallari and Julius Adebayo and Kori Inkpen and Martin T. Wells and Albert Gordo and Sarah Tan
Generative Models, Humans, Predictive Models: Who Is Worse at High-Stakes Decision Making?by Keri Mallari, Julius…
Summary of Multi-layer Feature Fusion with Cross-channel Attention-based U-net For Kidney Tumor Segmentation, by Fnu Neha et al.
Multi-Layer Feature Fusion with Cross-Channel Attention-Based U-Net for Kidney Tumor Segmentationby Fnu Neha, Arvind K.…
Summary of A Bayesian Framework For Clustered Federated Learning, by Peng Wu et al.
A Bayesian Framework for Clustered Federated Learningby Peng Wu, Tales Imbiriba, Pau ClosasFirst submitted to…
Summary of Mitigating Forgetting in Llm Supervised Fine-tuning and Preference Learning, by Heshan Fernando et al.
Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learningby Heshan Fernando, Han Shen, Parikshit Ram,…