Leonid Karlinsky

According to our database, Leonid Karlinsky authored at least 73 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards Multimodal In-Context Learning for Vision & Language Models.

Sivan Doveh, Shaked Perek, M. Jehanzeb Mirza, Amit Alfassy, Assaf Arbelle, Shimon Ullman, Leonid Karlinsky

CoRR, 2024

Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs.

Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Sivan Doveh, Jakub Micorek, Mateusz Kozinski, Hilde Kuehne, Horst Possegger

CoRR, 2024

Large Scale Generative AI Text Applied to Sports and Music.

Aaron K. Baughman, Stephen Hammer, Rahul Agarwal, Gozde Akay, Eduardo Morales, Tony Johnson, Leonid Karlinsky, Rogério Feris

CoRR, 2024

CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory.

Zexue He, Leonid Karlinsky, Donghyun Kim, Julian J. McAuley, Dmitry Krotov, Rogério Feris

CoRR, 2024

PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data.

Roei Herzig, Ofir Abramovich, Elad Ben-Avraham, Assaf Arbelle, Leonid Karlinsky, Ariel Shamir, Trevor Darrell, Amir Globerson

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

3VL: using Trees to teach Vision & Language models compositional concepts.

Nir Yellinek, Leonid Karlinsky, Raja Giryes

CoRR, 2023

GeRA: Label-Efficient Geometrically Regularized Alignment.

Dustin Klebe, Tal Shnitzer, Mikhail Yurochkin, Leonid Karlinsky, Justin Solomon

CoRR, 2023

Self-Specialization: Uncovering Latent Expertise within Large Language Models.

Junmo Kang, Hongyin Luo, Yada Zhu, James R. Glass, David D. Cox, Alan Ritter, Rogério Feris, Leonid Karlinsky

CoRR, 2023

TAP: Targeted Prompting for Task Adaptive Generation of Textual Training Instances for Visual Classification.

Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Horst Possegger, Rogério Feris, Horst Bischof

CoRR, 2023

Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers.

Yuan Gong, Sameer Khurana, Leonid Karlinsky, James R. Glass

CoRR, 2023

Comparison of Multilingual Self-Supervised and Weakly-Supervised Speech Pre-Training for Adaptation to Unseen Languages.

Andrew Rouditchenko, Sameer Khurana, Samuel Thomas, Rogério Feris, Leonid Karlinsky, Hilde Kuehne, David Harwath, Brian Kingsbury, James R. Glass

CoRR, 2023

Listen, Think, and Understand.

Yuan Gong, Hongyin Luo, Alexander H. Liu, Leonid Karlinsky, James R. Glass

CoRR, 2023

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies.

Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava

CoRR, 2023

Learning Human Action Recognition Representations Without Real Humans.

Howard Zhong, Samarth Mishra, Donghyun Kim, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Aude Oliva, Rogério Feris

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections.

Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Horst Possegger, Mateusz Kozinski, Rogério Feris, Horst Bischof

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models.

Sivan Doveh, Assaf Arbelle, Sivan Harary, Roei Herzig, Donghyun Kim, Paola Cascante-Bonilla, Amit Alfassy, Rameswar Panda, Raja Giryes, Rogério Feris, Shimon Ullman, Leonid Karlinsky

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning.

Zhen Wang, Rameswar Panda, Leonid Karlinsky, Rogério Feris, Huan Sun, Yoon Kim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning to Grow Pretrained Models for Efficient Transformer Training.

Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogério Feris, David Daniel Cox, Zhangyang Wang, Yoon Kim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Contrastive Audio-Visual Masked Autoencoder.

Yuan Gong, Andrew Rouditchenko, Alexander H. Liu, David Harwath, Leonid Karlinsky, Hilde Kuehne, James R. Glass

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Going Beyond Nouns With Vision & Language Models Using Synthetic Data.

Paola Cascante-Bonilla, Khaled Shehada, James Seale Smith, Sivan Doveh, Donghyun Kim, Rameswar Panda, Gül Varol, Aude Oliva, Vicente Ordonez, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge.

Wei Lin, Leonid Karlinsky, Nina Shvetsova, Horst Possegger, Mateusz Kozinski, Rameswar Panda, Rogério Feris, Hilde Kuehne, Horst Bischof

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval.

Andrew Rouditchenko, Yung-Sung Chuang, Nina Shvetsova, Samuel Thomas, Rogério Feris, Brian Kingsbury, Leonid Karlinsky, David Harwath, Hilde Kuehne, James R. Glass

Proceedings of the IEEE International Conference on Acoustics, 2023

Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs.

Roei Herzig, Alon Mendelson, Leonid Karlinsky, Assaf Arbelle, Rogério Feris, Trevor Darrell, Amir Globerson

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning.

James Seale Smith, Leonid Karlinsky, Vyshnavi Gutta, Paola Cascante-Bonilla, Donghyun Kim, Assaf Arbelle, Rameswar Panda, Rogério Feris, Zsolt Kira

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning.

James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle, Donghyun Kim, Rameswar Panda, David D. Cox, Diyi Yang, Zsolt Kira, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Teaching Structured Vision & Language Concepts to Vision & Language Models.

Sivan Doveh, Assaf Arbelle, Sivan Harary, Eli Schwartz, Roei Herzig, Raja Giryes, Rogério Feris, Rameswar Panda, Shimon Ullman, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Joint Audio and Speech Understanding.

Yuan Gong, Alexander H. Liu, Hongyin Luo, Leonid Karlinsky, James R. Glass

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022

Baby steps towards few-shot learning with multiple semantics.

Eli Schwartz, Leonid Karlinsky, Rogério Feris, Raja Giryes, Alexander M. Bronstein

Pattern Recognit. Lett., 2022

A Maximal Correlation Framework for Fair Machine Learning.

Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Schmidt Feris

Entropy, 2022

MAEDAY: MAE for few and zero shot AnomalY-Detection.

Eli Schwartz, Assaf Arbelle, Leonid Karlinsky, Sivan Harary, Florian Scheidegger, Sivan Doveh, Raja Giryes

CoRR, 2022

On the Transferability of Visual Features in Generalized Zero-Shot Learning.

Paola Cascante-Bonilla, Leonid Karlinsky, James Seale Smith, Yanjun Qi, Vicente Ordonez

CoRR, 2022

Teaching Structured Vision&Language Concepts to Vision&Language Models.

Sivan Doveh, Assaf Arbelle, Sivan Harary, Rameswar Panda, Roei Herzig, Eli Schwartz, Donghyun Kim, Raja Giryes, Rogério Feris, Shimon Ullman, Leonid Karlinsky

CoRR, 2022

On the Importance of Calibration in Semi-supervised Learning.

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

CoRR, 2022

VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models.

Felix Vogel, Nina Shvetsova, Leonid Karlinsky, Hilde Kuehne

CoRR, 2022

FETA: Towards Specializing Foundation Models for Expert Task Applications.

Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Kate Saenko, Peter W. J. Staar, Rogério Feris, Leonid Karlinsky

CoRR, 2022

Structured Video Tokens @ Ego4D PNR Temporal Localization Challenge 2022.

Elad Ben-Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson

CoRR, 2022

How Transferable are Video Representations Based on Synthetic Data?

Yo-whan Kim, Samarth Mishra, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Kate Saenko, Aude Oliva, Rogério Feris

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens.

Elad Ben-Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FETA: Towards Specializing Foundational Models for Expert Task Applications.

Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter W. J. Staar, Kate Saenko, Rogério Feris, Leonid Karlinsky

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Maximal Correlation Approach to Imposing Fairness in Machine Learning.

Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris

Proceedings of the IEEE International Conference on Acoustics, 2022

Self-Supervised Classification Network.

Elad Amrani, Leonid Karlinsky, Alexander M. Bronstein

Proceedings of the Computer Vision - ECCV 2022, 2022

Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data.

Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Richard Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogério Schmidt Feris

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Unsupervised Domain Generalization by Learning a Bridge Across Domains.

Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

MetAdapt: Meta-learned task-adaptive architecture for few-shot classification.

Sivan Doveh, Eli Schwartz, Chao Xue, Rogério Feris, Alexander M. Bronstein, Raja Giryes, Leonid Karlinsky

Pattern Recognit. Lett., 2021

CHARTER: heatmap-based multi-type chart data extraction.

Joseph Shtok, Sivan Harary, Ophir Azulai, Adi Raz Goldfarb, Assaf Arbelle, Leonid Karlinsky

CoRR, 2021

Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data.

Ashraful Islam, Chun-Fu (Richard) Chen, Rameswar Panda, Leonid Karlinsky, Rogério Feris, Richard J. Radke

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition.

Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris

Proceedings of the 9th International Conference on Learning Representations, 2021

A Broad Study on the Transferability of Visual Representations with Contrastive Learning.

Ashraful Islam, Chun-Fu Chen, Rameswar Panda, Leonid Karlinsky, Richard J. Radke, Rogério Feris

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Detector-Free Weakly Supervised Grounding by Separation.

Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Fine-Grained Angular Contrastive Learning With Coarse Labels.

Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

StarNet: towards Weakly Supervised Few-Shot Object Detection.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

StarNet: towards weakly supervised few-shot detection and explainable few-shot classification.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes

CoRR, 2020

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition.

Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris

Proceedings of the Computer Vision - ECCV 2020, 2020

TAFSSL: Task-Adaptive Feature Sub-Space Learning for Few-Shot Classification.

Moshe Lichtenstein, Prasanna Sattigeri, Rogério Feris, Raja Giryes, Leonid Karlinsky

Proceedings of the Computer Vision - ECCV 2020, 2020

A Broader Study of Cross-Domain Few-Shot Learning.

Yunhui Guo, Noel Codella, Leonid Karlinsky, James V. Codella, John R. Smith, Kate Saenko, Tajana Rosing, Rogério Feris

Proceedings of the Computer Vision - ECCV 2020, 2020

OnlineAugment: Online Data Augmentation with Less Domain Knowledge.

Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, Prasanna Sattigeri, Rogério Feris, Dimitris N. Metaxas

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning.

Yunhui Guo, Noel C. F. Codella, Leonid Karlinsky, John R. Smith, Tajana Rosing, Rogério Schmidt Feris

CoRR, 2019

A CNN based method for automatic mass detection and classification in mammograms.

Ayelet Akselrod-Ballin, Leonid Karlinsky, Sharon Alpert, Sharbell Y. Hasoul, Rami Ben-Ari, Ella Barkan

Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2019

RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection.

Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning.

Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

RepMet: Representative-based metric learning for classification and one-shot object detection.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein

CoRR, 2018

Delta-encoder: an effective sample synthesis method for few-shot object recognition.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Co-regularized Alignment for Unsupervised Domain Adaptation.

Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, Bill Freeman, Gregory W. Wornell

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography.

Ayelet Akselrod-Ballin, Leonid Karlinsky, Alon Hazan, Ran Bakalo, Ami Ben Horesh, Yoel Shoshan, Ella Barkan

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Domain specific convolutional neural nets for detection of architectural distortion in mammograms.

Rami Ben-Ari, Ayelet Akselrod-Ballin, Leonid Karlinsky, Sharbell Y. Hashoul

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Fine-Grained Recognition of Thousands of Object Categories with Single-Example Training.

Leonid Karlinsky, Joseph Shtok, Yochay Tzur, Asaf Tzadok

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Hybrid Remote Expert - an Emerging Pattern of Industrial Remote Support.

Ethan Hadar, Joseph Shtok, Benjamin Cohen, Yochay Tzur, Leonid Karlinsky

Proceedings of the Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering, 2017

2016

A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography.

Ayelet Akselrod-Ballin, Leonid Karlinsky, Sharon Alpert, Sharbell Y. Hasoul, Rami Ben-Ari, Ella Barkan

Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016

2012

Using Linking Features in Learning Non-parametric Part Models.

Leonid Karlinsky, Shimon Ullman

Proceedings of the Computer Vision - ECCV 2012, 2012

2010

Using body-anchored priors for identifying actions in single images.

Leonid Karlinsky, Michael Dinerstein, Shimon Ullman

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

The chains model for detecting parts by their context.

Leonid Karlinsky, Michael Dinerstein, Daniel Harari, Shimon Ullman

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009

Unsupervised feature optimization (UFO): Simultaneous selection of multiple features with their detection parameters.

Leonid Karlinsky, Michael Dinerstein, Shimon Ullman

Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008

Unsupervised Classification and Part Localization by Consistency Amplification.

Leonid Karlinsky, Michael Dinerstein, Dan Levi, Shimon Ullman

Proceedings of the Computer Vision, 2008