Summary of Graph Pre-training Models Are Strong Anomaly Detectors, by Jiashun Cheng et al.
Graph Pre-Training Models Are Strong Anomaly Detectorsby Jiashun Cheng, Zinan Zheng, Yang Liu, Jianheng Tang,…
Summary of Scaling Up Masked Diffusion Models on Text, by Shen Nie et al.
Scaling up Masked Diffusion Models on Textby Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang,…
Summary of Kvsharer: Efficient Inference Via Layer-wise Dissimilar Kv Cache Sharing, by Yifei Yang et al.
KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharingby Yifei Yang, Zouying Cao, Qiguang Chen,…
Summary of Automated Defect Detection and Grading Of Piarom Dates Using Deep Learning, by Nasrin Azimi et al.
Automated Defect Detection and Grading of Piarom Dates Using Deep Learningby Nasrin Azimi, Danial Mohammad…
Summary of Towards Understanding the Fragility Of Multilingual Llms Against Fine-tuning Attacks, by Samuele Poppi et al.
Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacksby Samuele Poppi, Zheng-Xin Yong, Yifei…
Summary of Multi-draft Speculative Sampling: Canonical Architectures and Theoretical Limits, by Ashish Khisti et al.
Multi-Draft Speculative Sampling: Canonical Architectures and Theoretical Limitsby Ashish Khisti, M.Reza Ebrahimi, Hassan Dbouk, Arash…
Summary of Asynchronous Rlhf: Faster and More Efficient Off-policy Rl For Language Models, by Michael Noukhovitch et al.
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Modelsby Michael Noukhovitch, Shengyi Huang,…
Summary of Fast Inference For Augmented Large Language Models, by Rana Shahout et al.
Fast Inference for Augmented Large Language Modelsby Rana Shahout, Cong Liang, Shiji Xin, Qianru Lao,…
Summary of Hamiltonian Matching For Symplectic Neural Integrators, by Priscilla Canizares et al.
Hamiltonian Matching for Symplectic Neural Integratorsby Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry, Zakhar…
Summary of Augmenting Training Data with Vector-quantized Variational Autoencoder For Classifying Rf Signals, by Srihari Kamesh Kompella et al.
Augmenting Training Data with Vector-Quantized Variational Autoencoder for Classifying RF Signalsby Srihari Kamesh Kompella, Kemal…