Research

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

Title	Authors	Year	Source
Dimensionally Reduced Open-World Clustering: DROWCULA	Erencem Ozbey, Dimitrios I. Diochnos	2025	arxiv 2509.07184
ProfilingAgent: Profiling-Guided Agentic Reasoning for Adaptive Model Optimization	Sadegh Jafari, Aishwarya Sarkar, Mohiuddin Bilwal	2025	arxiv 2509.05584
CSDformer: A Conversion Method for Fully Spike-Driven Transformer	Yuhao Zhang, Chengjun Zhang, Di Wu	2025	arxiv 2509.17461
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models	Tianzhe Chu, Shengbang Tong, Tianjiao Ding	2023	arxiv 2306.05272
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models	Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri	2023	arxiv 2311.18237
FYI: Flip Your Images for Dataset Distillation	Byunggwan Son, Youngmin Oh, Donghyeon Baek	2024	arxiv 2407.08113
Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples	Min Gu Kwak, Hyungu Kahng, Seoung Bum Kim	2024	arxiv 2408.01872
Image complexity based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning	Debanjali Bhattacharya, Neelam Sinha, Yashwanth R.	2023	arxiv 2311.08417
Learning high-level visual representations from a child's perspective without strong inductive biases	A. Emin Orhan, Brenden M. Lake	2023	arxiv 2305.15372
Smooth Adversarial Training	Cihang Xie, Mingxing Tan, Boqing Gong	2020	arxiv 2006.14536
FREE: Feature Refinement for Generalized Zero-Shot Learning	Shiming Chen, Wenjie Wang, Beihao Xia	2021	arxiv 2107.13807
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks	Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala	2021	arxiv 2108.08903
Damage detection using in-domain and cross-domain transfer learning	Zaharah A. Bukhsh, Nils Jansen, Aaqib Saeed	2021	arxiv 2102.03858
A Closer Look at Few-Shot Video Classification: A New Baseline and Benchmark	Zhenxi Zhu, Limin Wang, Sheng Guo	2021	arxiv 2110.12358
Why Do Better Loss Functions Lead to Less Transferable Features?	Simon Kornblith, Ting Chen, Honglak Lee	2020	arxiv 2010.16402
A Framework for Learning Ante-hoc Explainable Models via Concepts	Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar	2021	arxiv 2108.11761
Input-Specific Robustness Certification for Randomized Smoothing	Ruoxin Chen, Jie Li, Junchi Yan	2021	arxiv 2112.12084
BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch	Souvik Kundu, Shikai Wang, Qirui Sun	2021	arxiv 2112.13843
Robust Contrastive Learning Using Negative Samples with Diminished Semantics	Songwei Ge, Shlok Mishra, Haohan Wang	2021	arxiv 2110.14189
Fixing the train-test resolution discrepancy	Hugo Touvron, Andrea Vedaldi, Matthijs Douze	2019	arxiv 1906.06423

Search results