Summary of Question Answering System Of Bridge Design Specification Based on Large Language Model, by Leye Zhang et al.
Question answering system of bridge design specification based on large language modelby Leye Zhang, Xiangxiang…
Summary of Segment Anything Model For Grain Characterization in Hard Drive Design, by Kai Nichols et al.
Segment Anything Model for Grain Characterization in Hard Drive Designby Kai Nichols, Matthew Hauwiller, Nicholas…
Summary of Pcgrl+: Scaling, Control and Generalization in Reinforcement Learning Level Generators, by Sam Earle et al.
PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generatorsby Sam Earle, Zehua Jiang, Julian…
Summary of Dynamics Of Meta-learning Representation in the Teacher-student Scenario, by Hui Wang et al.
Dynamics of Meta-learning Representation in the Teacher-student Scenarioby Hui Wang, Cho Tung Yip, Bo LiFirst…
Summary of Cell-ontology Guided Transcriptome Foundation Model, by Xinyu Yuan et al.
Cell-ontology guided transcriptome foundation modelby Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao,…
Summary of Multi-source Knowledge-based Hybrid Neural Framework For Time Series Representation Learning, by Sagar Srinivas Sakhinana et al.
Multi-Source Knowledge-Based Hybrid Neural Framework for Time Series Representation Learningby Sagar Srinivas Sakhinana, Krishna Sai…
Summary of Self-supervised Learning For Geospatial Ai: a Survey, by Yile Chen et al.
Self-supervised Learning for Geospatial AI: A Surveyby Yile Chen, Weiming Huang, Kaiqi Zhao, Yue Jiang,…
Summary of Transformers Are Minimax Optimal Nonparametric In-context Learners, by Juno Kim et al.
Transformers are Minimax Optimal Nonparametric In-Context Learnersby Juno Kim, Tai Nakamaki, Taiji SuzukiFirst submitted to…
Summary of Elder: Enhancing Lifelong Model Editing with Mixture-of-lora, by Jiaang Li et al.
ELDER: Enhancing Lifelong Model Editing with Mixture-of-LoRAby Jiaang Li, Quan Wang, Zhongnan Wang, Yongdong Zhang,…
Summary of Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness, By Viacheslav Komisarenko and Meelis Kull
Improving Calibration by Relating Focal Loss, Temperature Scaling, and Propernessby Viacheslav Komisarenko, Meelis KullFirst submitted…