Fetching the paper…
Reading the bibliography…
Deep neural networks are becoming increasingly pervasive in academia and industry, matching and surpassing human performance on a wide variety of fields and related tasks.
Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
Earlier work this paper cites.
Long short-term memory
Jürgen Schmidhuber, Sepp Hochreiter, et al · 1997
Earlier work this paper cites.
Automating the construction of internet portals with machine learning
Andrew Kachites McCallum, Kamal Nigam, Jason Rennie, and Kristie Seymore · 2000
Earlier work this paper cites.
Direct and indirect effects
Judea Pearl · 2001
Earlier work this paper cites.
Safety critical systems: challenges and directions
John C Knight · 2002
Earlier work this paper cites.
Machine learning , volume 1
Tom Michael Mitchell et al · 2007
Earlier work this paper cites.
Stably maintained dendritic spines are associated with lifelong memories
Guang Yang, Feng Pan, and Wen-Biao Gan · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Cifar-10 (canadian institute for advanced research). 2009
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Mnist handwritten digit database
Yann LeCun, Corinna Cortes, and CJ Burges · 2010
Earlier work this paper cites.
Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
Earlier work this paper cites.
Robust airborne collision avoidance through dynamic programming
Mykel J Kochenderfer and JP Chryssanthacopoulos · 2011
Earlier work this paper cites.
Report on the 11th iwslt evaluation campaign
Mauro Cettolo, Jan Niehues, Sebastian Stüker, Luisa Bentivogli, and Marcello Federico · 2014
Earlier work this paper cites.
Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
Earlier work this paper cites.
Branch-specific dendritic ca2+ spikes cause persistent synaptic plasticity
Joseph Cichon and Wen-Biao Gan · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
End-to-end memory networks
Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et al · 2015
Earlier work this paper cites.
Towards making systems forget with machine unlearning
Yinzhi Cao and Junfeng Yang · 2015
Earlier work this paper cites.
Computational principles of synaptic memory consolidation
Marcus K Benna and Stefano Fusi · 2016
Earlier work this paper cites.
A survey of transfer learning
Karl Weiss, Taghi M Khoshgoftaar, and DingDing Wang · 2016
Earlier work this paper cites.
Rgbd datasets: Past, present and future
Michael Firman · 2016
Earlier work this paper cites.
Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher · 2016
Earlier work this paper cites.
Policy compression for aircraft collision avoidance systems
Kyle D. Julian, Jessica Lopez, Jeffrey S. Brush, Michael P. Owen, and Mykel J. Kochenderfer · 2016
Earlier work this paper cites.
David Ha, Andrew Dai, and Quoc V Le · 2016
Earlier work this paper cites.
Meta-learning with memory-augmented neural networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap · 2016
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
Earlier work this paper cites.
Zero-shot relation extraction via reading comprehension
Omer Levy, Minjoon Seo, Eunsol Choi, and Luke Zettlemoyer · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Reluplex: An efficient smt solver for verifying deep neural networks
Guy Katz, Clark Barrett, David L Dill, Kyle Julian, and Mykel J Kochenderfer · 2017
Earlier work this paper cites.
Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
Earlier work this paper cites.
Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
Earlier work this paper cites.
Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2017
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Fever: a large-scale dataset for fact extraction and verification
J Thorne, A Vlachos, C Christodoulopoulos, and A Mittal · 2018
Earlier work this paper cites.
Conditional neural processes
Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Rezende, and SM Ali Eslami · 2018
Earlier work this paper cites.
Deep learning for computer vision: A brief review
Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis, Eftychios Protopapadakis, et al · 2018
Earlier work this paper cites.
T-REx: A large scale alignment of natural language with knowledge base triples
Hady Elsahar, Pavlos Vougiouklis, Arslen Remaci, Christophe Gravier, Jonathon Hare, Frederique Laforest, and Elena Simperl · 2018
Earlier work this paper cites.
Formal security analysis of neural networks using symbolic intervals
Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, and Suman Jana · 2018
Earlier work this paper cites.
Measuring catastrophic forgetting in neural networks
Ronald Kemker, Marc McClure, Angelina Abitino, Tyler Hayes, and Christopher Kanan · 2018
Earlier work this paper cites.
Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
Cited alongside, same era.
Meta-learning for semi-supervised few-shot classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B Tenenbaum, Hugo Larochelle, and Richard S Zemel · 2018
Cited alongside, same era.
Evolved policy gradients
Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly Stadie, Filip Wolski, OpenAI Jonathan Ho, and Pieter Abbeel · 2018
Cited alongside, same era.
FiLM: Visual Reasoning with a General Conditioning Layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron Courville · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
Cited alongside, same era.
Generating informative and diverse conversational responses via adversarial information maximization
A principled approach to failure analysis and model repairment: Demonstration in medical imaging
Thomas Henn, Yasukazu Sakamoto, Clément Jacquet, Shunsuke Yoshizawa, Masamichi Andou, Stephen Tchen, Ryosuke Saga, Hiroyuki Ishihara, Katsuhiko Shimizu, Yingzhen Li, et al · 2021
Later among the works it cites.
Pali: A jointly-scaled multilingual language-image model
Xi Chen, Xiao Wang, Soravit Changpinyo, AJ Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, et al · 2022
Later among the works it cites.
Alexatm 20b: Few-shot learning using a large-scale multilingual seq2seq model
Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, Rahul Gupta, Wael Hamza, Haidar Khan, Charith Peris, Stephen Rawls, Andy Rosenbaum, Anna Rumshisky, et al · 2022
Later among the works it cites.
Machine learning in medical applications: A review of state-of-the-art methods
Mohammad Shehab, Laith Abualigah, Qusai Shambour, Muhannad A Abu-Hashem, Mohd Khaled Yousef Shambour, Ahmed Izzat Alsalibi, and Amir H Gandomi · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, and Bill Dolan · 2018
Cited alongside, same era.
Multimodal machine learning: A survey and taxonomy
Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency · 2018
Cited alongside, same era.
The bottom-up evolution of representations in the transformer: A study with machine translation and language modeling objectives
Elena Voita, Rico Sennrich, and Ivan Titov · 2019
Cited alongside, same era.
Analysis methods in neural language processing: A survey
Yonatan Belinkov and James Glass · 2019
Cited alongside, same era.
Mnist-c: A robustness benchmark for computer vision
Norman Mu and Justin Gilmer · 2019
Cited alongside, same era.
Overcoming catastrophic forgetting with unlabeled data in the wild
Kibok Lee, Kimin Lee, Jinwoo Shin, and Honglak Lee · 2019
Cited alongside, same era.
Introduction to Natural Language Processing
Jacob Eisenstein · 2019
Cited alongside, same era.
Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, and Marzyeh Ghassemi · 2022
Later among the works it cites.
Computer vision: algorithms and applications
Richard Szeliski · 2022
Later among the works it cites.
Alexa teacher model: Pretraining and distilling multi-billion-parameter encoders for natural language understanding systems
Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudre, Dilek Hakkani-Tur, Wael Hamza, Jonathan J. Hüser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Lizhen Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gokhan Tur, and Prem Natarajan · 2022
Later among the works it cites.
Pre-trained language models and their applications
Haifeng Wang, Jiwei Li, Hua Wu, Eduard Hovy, and Yu Sun · 2022
Later among the works it cites.
A survey on automated fact-checking
Zhijiang Guo, Michael Schlichtkrull, and Andreas Vlachos · 2022
Later among the works it cites.
FairLex: A multilingual benchmark for evaluating fairness in legal text processing
Ilias Chalkidis, Tommaso Pasini, Sheng Zhang, Letizia Tomada, Sebastian Schwemer, and Anders Søgaard · 2022
Later among the works it cites.
Transformer memory as a differentiable search index
Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, et al · 2022
Later among the works it cites.
Knowledge neurons in pretrained transformers
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei · 2022
Later among the works it cites.
Calibrating factual knowledge in pretrained language models
Qingxiu Dong, Damai Dai, Yifan Song, Jingjing Xu, Zhifang Sui, and Lei Li · 2022
Later among the works it cites.
LoRA: Low-rank adaptation of large language models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
Later among the works it cites.
A survey of machine unlearning
Thanh Tam Nguyen, Thanh Trung Huynh, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, and Quoc Viet Hung Nguyen · 2022
Later among the works it cites.
Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi · 2022
Later among the works it cites.
Transformer-patcher: One mistake worth one neuron
Zeyu Huang, Yikang Shen, Xiaofeng Zhang, Jie Zhou, Wenge Rong, and Zhang Xiong · 2023
Closest in time.
Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
Closest in time.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
Closest in time.
Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Mohsen Soori, Behrooz Arezoo, and Roza Dastres · 2023
Closest in time.
Editing large language models: Problems, methods, and opportunities
Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, and Ningyu Zhang · 2023
Closest in time.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
Closest in time.
Repairing deep neural networks based on behavior imitation
Zhen Liang, Taoran Wu, Changyuan Zhao, Wanwei Liu, Bai Xue, Wenjing Yang, and Ji Wang · 2023
Closest in time.
Editable graph neural network for node classifications
Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, and Xia Hu · 2023
Closest in time.
A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning
Martin Mundt, Yongwon Hong, Iuliia Pliushch, and Visvanathan Ramesh · 2023
Closest in time.
Massive editing for large language models via meta learning
Chenmien Tan, Ge Zhang, and Jie Fu · 2023
Closest in time.
A survey on evaluation of large language models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al · 2023
Closest in time.
Analyzing transformers in embedding space
Guy Dar, Mor Geva, Ankit Gupta, and Jonathan Berant · 2023
Closest in time.
Editing commonsense knowledge in gpt
Anshita Gupta, Debanjan Mondal, Akshay Krishna Sheshadri, Wenlong Zhao, Xiang Lorraine Li, Sarah Wiegreffe, and Niket Tandon · 2023
Closest in time.
Peter Hase, Mohit Bansal, Been Kim, and Asma Ghandeharioun · 2023
Closest in time.
Knowledge unlearning for llms: Tasks, methods, and challenges
Nianwen Si, Hao Zhang, Heyu Chang, Wenlin Zhang, Dan Qu, and Weiqiang Zhang · 2023
Closest in time.
On the effectiveness of parameter-efficient fine-tuning
Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam, Lidong Bing, and Nigel Collier · 2023
Closest in time.
In-context learning creates task vectors
Roee Hendel, Mor Geva, and Amir Globerson · 2023
Closest in time.
Machine un-learning: An overview of techniques, applications, and future directions
Siva Sai, Uday Mittal, Vinay Chamola, Kaizhu Huang, Indro Spinelli, Simone Scardapane, Zhiyuan Tan, and Amir Hussain · 2023
Closest in time.
John Hewitt, John Thickstun, Christopher D Manning, and Percy Liang · 2023
Closest in time.
A comprehensive survey on pretrained foundation models: A history from bert to chatgpt
Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, et al · 2023
Closest in time.
Editing language model-based knowledge graph embeddings
Siyuan Cheng, Ningyu Zhang, Bozhong Tian, Xi Chen, Qingbin Liu, and Huajun Chen · 2024
Closest in time.
Pmet: Precise model editing in a transformer
Xiaopeng Li, Shasha Li, Shezheng Song, Jing Yang, Jun Ma, and Jie Yu · 2024
Closest in time.
Parameter-efficient fine-tuning for large models: A comprehensive survey
Zeyu Han, Chao Gao, Jinyang Liu, Sai Qian Zhang, et al · 2024
Closest in time.
Melo: Enhancing model editing with neuron-indexed dynamic lora
Lang Yu, Qin Chen, Jie Zhou, and Liang He · 2024
Closest in time.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
Closest in time.
Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet
Adly Templeton · 2024
Closest in time.