Summary of Scaling Laws Across Model Architectures: a Comparative Analysis Of Dense and Moe Models in Large Language Models, by Siqi Wang et al.
Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large…
Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large…
LOTOS: Layer-wise Orthogonalization for Training Robust Ensemblesby Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun ChandrasekaranFirst submitted to…
Building Damage Assessment in Conflict Zones: A Deep Learning Approach Using Geospatial Sub-Meter Resolution Databy…
RAFT: Realistic Attacks to Fool Text Detectorsby James Wang, Ran Li, Junfeng Yang, Chengzhi MaoFirst…
One-step Noisy Label Mitigationby Hao Li, Jiayang Gu, Jingkuan Song, An Zhang, Lianli GaoFirst submitted…
CableInspect-AD: An Expert-Annotated Anomaly Detection Datasetby Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani, Aldo Zaimi, Ge…
Model Selection with a Shapelet-based Distance Measure for Multi-source Transfer Learning in Time Series Classificationby…
Spatial Reasoning and Planning for Deep Embodied Agentsby Shu IshidaFirst submitted to arxiv on: 28…
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Modelsby Gongfan Fang, Hongxu Yin, Saurav Muralidharan, Greg…
GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learningby Zhe-Rui Yang, Jindong Han, Chang-Dong Wang,…