Summary of Navigation World Models, by Amir Bar et al.
Navigation World Modelsby Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, Yann LeCunFirst submitted to…
Summary of Not All Adapters Matter: Selective Adapter Freezing For Memory-efficient Fine-tuning Of Language Models, by Hyegang Son et al.
Not All Adapters Matter: Selective Adapter Freezing for Memory-Efficient Fine-Tuning of Language Modelsby Hyegang Son,…
Summary of Survey Of Different Large Language Model Architectures: Trends, Benchmarks, and Challenges, by Minghao Shao et al.
Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challengesby Minghao Shao, Abdul Basit,…
Summary of Theoretical Limitations Of Multi-layer Transformer, by Lijie Chen et al.
Theoretical limitations of multi-layer Transformerby Lijie Chen, Binghui Peng, Hongxun WuFirst submitted to arxiv on:…
Summary of Gqwformer: a Quantum-based Transformer For Graph Representation Learning, by Lei Yu et al.
GQWformer: A Quantum-based Transformer for Graph Representation Learningby Lei Yu, Hongyang Chen, Jingsong Lv, Linyao…
Summary of Fgatt: a Robust Framework For Wireless Data Imputation Using Fuzzy Graph Attention Networks and Transformer Encoders, by Jinming Xing et al.
FGATT: A Robust Framework for Wireless Data Imputation Using Fuzzy Graph Attention Networks and Transformer…
Summary of Revisiting the Initial Steps in Adaptive Gradient Descent Optimization, by Abulikemu Abuduweili and Changliu Liu
Revisiting the Initial Steps in Adaptive Gradient Descent Optimizationby Abulikemu Abuduweili, Changliu LiuFirst submitted to…
Summary of Rehub: Linear Complexity Graph Transformers with Adaptive Hub-spoke Reassignment, by Tomer Borreda et al.
ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignmentby Tomer Borreda, Daniel Freedman, Or LitanyFirst…
Summary of Convolutional Transformer Neural Collaborative Filtering, by Pang Li et al.
Convolutional Transformer Neural Collaborative Filteringby Pang Li, Shahrul Azman Mohd Noah, Hafiz Mohd SarimFirst submitted…
Summary of Float: Generative Motion Latent Flow Matching For Audio-driven Talking Portrait, by Taekyung Ki et al.
FLOAT: Generative Motion Latent Flow Matching for Audio-driven Talking Portraitby Taekyung Ki, Dongchan Min, Gyeongsu…