Summary of Prenet: Leveraging Computational Features to Predict Deep Neural Network Training Time, by Alireza Pourali et al.
PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Timeby Alireza Pourali, Arian Boukani,…
PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Timeby Alireza Pourali, Arian Boukani,…
PCA-Featured Transformer for Jamming Detection in 5G UAV Networksby Joseanne Viana, Hamed Farkhari, Pedro Sebastiao,…
Large Language Models on Small Resource-Constrained Systems: Performance Characterization, Analysis and Trade-offsby Liam Seymour, Basar…
An Enhanced Text Compression Approach Using Transformer-based Language Modelsby Chowdhury Mofizur Rahman, Mahbub E Sobhani,…
A Universal Model for Human Mobility Predictionby Qingyue Long, Yuan Yuan, Yong LiFirst submitted to…
Tokenphormer: Structure-aware Multi-token Graph Transformer for Node Classificationby Zijie Zhou, Zhaoqi Lu, Xuekai Wei, Rongqin…
IDOL: Instant Photorealistic 3D Human Creation from a Single Imageby Yiyu Zhuang, Jiaxi Lv, Hao…
A Full Transformer-based Framework for Automatic Pain Estimation using Videosby Stefanos Gkikas, Manolis TsiknakisFirst submitted…
LMFusion: Adapting Pretrained Language Models for Multimodal Generationby Weijia Shi, Xiaochuang Han, Chunting Zhou, Weixin…
MARIA: a Multimodal Transformer Model for Incomplete Healthcare Databy Camillo Maria Caruso, Paolo Soda, Valerio…