Fetching the paper…
Reading the bibliography…
While vision-language pre-trained models (VL-PTMs) have advanced multimodal research in recent years, their mastery in a few languages like English restricts their applicability in broader communities.
On Tiny Episodic Memories in Continual Learning
Chaudhry, A.; Rohrbach, M.; Elhoseiny, M.; Ajanthan, T.; Dokania, P. K.; Torr, P. H. S.; and Ranzato, M. 2019 · 1902
Earlier work this paper cites.
Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
McCloskey, M.; and Cohen, N. J. 1989 · 1989
Earlier work this paper cites.
Improving Predictive Inference under Covariate Shift by Weighting the Log-Likelihood Function
Shimodaira, H. 2000 · 2000
Earlier work this paper cites.
Microsoft COCO Captions: Data Collection and Evaluation Server
Chen, X.; Fang, H.; Lin, T.-Y.; Vedantam, R.; Gupta, S.; Dollar, P.; and Zitnick, C. L. 2015 · 2015
Earlier work this paper cites.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S.; and Szegedy, C. 2015 · 2015
Earlier work this paper cites.
Deep Visual-Semantic Alignments for Generating Image Descriptions
Karpathy, A.; and Fei-Fei, L. 2015 · 2015
Earlier work this paper cites.
Multi30K: Multilingual English-German Image Descriptions
Elliott, D.; Frank, S.; Sima’an, K.; and Specia, L. 2016 · 2016
Earlier work this paper cites.
Neural Machine Translation of Rare Words with Subword Units
Sennrich, R.; Haddow, B.; and Birch, A. 2016 · 2016
Earlier work this paper cites.
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Chaudhari, P.; Choromanska, A.; Soatto, S.; LeCun, Y.; Baldassi, C.; Borgs, C.; Chayes, J.; Sagun, L.; and Zecchina, R. 2017 · 2017
Earlier work this paper cites.
Overcoming Catastrophic Forgetting in Neural Networks
Kirkpatrick, J.; Pascanu, R.; Rabinowitz, N.; Veness, J.; Desjardins, G.; Rusu, A. A.; Milan, K.; Quan, J.; Ramalho, T.; Grabska-Barwinska, A.; Hassabis, D.; Clopath, C.; Kumaran, D.; and Hadsell, R. 2017 · 2017
Earlier work this paper cites.
Attention Is All You Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Earlier work this paper cites.
Progress & Compress: A Scalable Framework for Continual Learning
Schwarz, J.; Czarnecki, W.; Luketina, J.; Grabska-Barwinska, A.; Teh, Y. W.; Pascanu, R.; and Hadsell, R. 2018 · 2018
Earlier work this paper cites.
Conceptual Captions: A Cleaned, Hypernymed, Image Alt-Text Dataset For Automatic Image Captioning
Sharma, P.; Ding, N.; Goodman, S.; and Soricut, R. 2018 · 2018
Earlier work this paper cites.
Representation Learning with Contrastive Predictive Coding
van den Oord, A.; Li, Y.; and Vinyals, O. 2018 · 2018
Earlier work this paper cites.
Lifelong Learning with Dynamically Expandable Networks
Yoon, J.; Yang, E.; Lee, J.; and Hwang, S. J. 2018 · 2018
Earlier work this paper cites.
Task-Free Continual Learning
Aljundi, R.; Kelchtermans, K.; and Tuytelaars, T. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
Earlier work this paper cites.
Parameter-Efficient Transfer Learning for NLP
Houlsby, N.; Giurgiu, A.; Jastrzebski, S.; Morrone, B.; Laroussilhe, Q. D.; Gesmundo, A.; Attariyan, M.; and Gelly, S. 2019 · 2019
Earlier work this paper cites.
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild
Lee, K.; Lee, K.; Shin, J.; and Lee, H. 2019 · 2019
Earlier work this paper cites.
Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
Li, X.; Zhou, Y.; Wu, T.; Socher, R.; and Xiong, C. 2019 · 2019
Earlier work this paper cites.
Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
Cited alongside, same era.
Continual Lifelong Learning in Natural Language Processing: A Survey
Biesialska, M.; Biesialska, K.; and Costa-jussà, M. R. 2020 · 2020
Cited alongside, same era.
Dark Experience for General Continual Learning: A Strong, Simple Baseline
Buzzega, P.; Boschini, M.; Porrello, A.; Abati, D.; and CALDERARA, SIMONE. 2020 · 2020
Cited alongside, same era.
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
Ke, Z.; Liu, B.; and Huang, X. 2020 · 2020
Cited alongside, same era.
BART: Denoising Sequence-to-Sequence Pre-Training for Natural Language Generation, Translation, and Comprehension
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2020 · 2020
Cited alongside, same era.
AdapterHub: A Framework for Adapting Transformers
Flamingo: A Visual Language Model for Few-Shot Learning
Alayrac, J.-B.; Donahue, J.; Luc, P.; Miech, A.; Barr, I.; Hasson, Y.; Lenc, K.; Mensch, A.; Millican, K.; Reynolds, M.; Ring, R.; Rutherford, E.; Cabi, S.; Han, T.; Gong, Z.; Samangooei, S.; Monteiro, M.; Menick, J.; Borgeaud, S.; Brock, A.; Nematzadeh, A.; Sharifzadeh, S.; Binkowski, M.; Barreira, R.; Vinyals, O.; Zisserman, A.; and Simonyan, K. 2022 · 2022
Later among the works it cites.
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages
Bugliarello, E.; Liu, F.; Pfeiffer, J.; Reddy, S.; Elliott, D.; Ponti, E. M.; and Vulić, I. 2022 · 2022
Later among the works it cites.
Cross-Lingual and Multilingual CLIP
Carlsson, F.; Eisen, P.; Rekathati, F.; and Sahlgren, M. 2022 · 2022
Later among the works it cites.
Don’t Stop Learning: Towards Continual Learning for the CLIP Model
Ding, Y.; Liu, L.; Tian, C.; Yang, J.; and Ding, H. 2022 · 2022
Later among the works it cites.
Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends
Gan, Z.; Li, L.; Li, C.; Wang, L.; Liu, Z.; and Gao, J. 2022 · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pfeiffer, J.; Rücklé, A.; Poth, C.; Kamath, A.; Vulić, I.; Ruder, S.; Cho, K.; and Gurevych, I. 2020 · 2020
Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Cited alongside, same era.
Making Monolingual Sentence Embeddings Multilingual Using Knowledge Distillation
Reimers, N.; and Gurevych, I. 2020 · 2020
Cited alongside, same era.
SS-IL: Separated Softmax for Incremental Learning
Ahn, H.; Kwak, J.; Lim, S.; Bang, H.; Kim, H.; and Moon, T. 2021 · 2021
Cited alongside, same era.
Continual Learning in Multilingual NMT via Language-Specific Embeddings
Berard, A. 2021 · 2021
Cited alongside, same era.
Co2L: Contrastive Continual Learning
Cha, H.; Lee, J.; and Shin, J. 2021 · 2021
Cited alongside, same era.
From Bilingual to Multilingual Neural-based Machine Translation by Incremental Training
Escolano, C.; Costa-Jussà, M. R.; and Fonollosa, J. A. R. 2021 · 2021
Cited alongside, same era.
Later among the works it cites.
LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2022 · 2022
Later among the works it cites.
Entropy-Based Vocabulary Substitution for Incremental Learning in Multilingual Neural Machine Translation
Huang, K.; Li, P.; Ma, J.; and Liu, Y. 2022 · 2022
Later among the works it cites.
P-Tuning: Prompt Tuning Can Be Comparable to Fine-Tuning Across Scales and Tasks
Liu, X.; Ji, K.; Fu, Y.; Tam, W.; Du, Z.; Yang, Z.; and Tang, J. 2022 · 2022
Later among the works it cites.
Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset
Thapliyal, A. V.; Pont Tuset, J.; Chen, X.; and Soricut, R. 2022 · 2022
Later among the works it cites.
CLIP Model Is an Efficient Continual Learner
Thengane, V.; Khan, S.; Hayat, M.; and Khan, F. 2022 · 2022
Later among the works it cites.
Pretrained Language Model in Continual Learning: A Comparative Study
Wu, T.; Caccia, M.; Li, Z.; Li, Y.-F.; Qi, G.; and Haffari, G. 2022 · 2022
Later among the works it cites.
LiT: Zero-Shot Transfer With Locked-Image Text Tuning
Zhai, X.; Wang, X.; Mustafa, B.; Steiner, A.; Keysers, D.; Kolesnikov, A.; and Beyer, L. 2022 · 2022
Later among the works it cites.
CLLE: A Benchmark for Continual Language Learning Evaluation in Multilingual Machine Translation
Zhang, H.; Zhang, S.; Xiang, Y.; Liang, B.; Su, J.; Miao, Z.; Wang, H.; and Xu, R. 2022 · 2022
Later among the works it cites.
Multi-Lingual Acquisition on Multimodal Pre-Training for Cross-Modal Retrieval
Zhang, L.; Hu, A.; and Jin, Q. 2022 · 2022
Later among the works it cites.
A Unified Continual Learning Framework with General Parameter-Efficient Tuning
Gao, Q.; Zhao, C.; Sun, Y.; Xi, T.; Zhang, G.; Ghanem, B.; and Zhang, J. 2023 · 2023
Later among the works it cites.
Cross-Lingual Continual Learning
M’hamdi, M.; Ren, X.; and May, J. 2023 · 2023
Later among the works it cites.
CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning
Smith, J. S.; Karlinsky, L.; Gutta, V.; Cascante-Bonilla, P.; Kim, D.; Arbelle, A.; Panda, R.; Feris, R.; and Kira, Z. 2023 · 2023
Later among the works it cites.
A Comprehensive Survey of Continual Learning: Theory, Method and Application
Wang, L.; Zhang, X.; Su, H.; and Zhu, J. 2023 · 2023
Later among the works it cites.
Concept-Aware Video Captioning: Describing Videos With Effective Prior Information
Yang, B.; Cao, M.; and Zou, Y. 2023 · 2023
Later among the works it cites.
MultiCapCLIP: Auto-Encoding Prompts for Zero-Shot Multilingual Visual Captioning
Yang, B.; Liu, F.; Wu, X.; Wang, Y.; Sun, X.; and Zou, Y. 2023 · 2023
Later among the works it cites.