Shafiq R. Joty
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 24 papers; trusts 1,567 researchers and is trusted by 62 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 810 citations into it; #4,203 of 35,345 by trust here, #1,790 by citations
- Natural Language Processing — 487 citations into it; #2,546 of 5,688 by trust here, #1,274 by citations
- Computer Vision and Pattern Recognition — 391 citations into it; #6,252 of 21,575 by trust here, #2,594 by citations
- Evaluation & Benchmarks — 184 citations into it
- Large Language Models — 168 citations into it
- Multimodal Learning — 119 citations into it; #561 of 1,211 by trust here, #363 by citations
- Information Systems — 112 citations into it; #5,131 of 8,771 by trust here, #1,265 by citations
- Representation & Self-Supervised Learning — 90 citations into it; #2,692 of 3,145 by trust here, #939 by citations
Whom Shafiq R. Joty trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Kaiming He
- Alex Krizhevsky
- Yann LeCun
- Alex Graves
- Oriol Vinyals
- Jimmy Ba
Who trusts Shafiq R. Joty overall
- Zixuan Ke
- Barbara Plank
- Wenya Wang
- Kurt Shuster
- Zhe Gan
- Sarah Wiegreffe
- Héctor Martínez Alonso
- Alessandra Cervone
- Wei-Ning Hsu
- Junnan Li
Papers from Shafiq R. Joty's perspective
Ordered by how strongly the researchers Shafiq R. Joty trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Align before Fuse: Vision and Language Representation Learning with Momentum Distillation (2021) — 2,847 citations
- GeDi: Generative Discriminator Guided Sequence Generation (2020) — 516 citations
- Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models (2017) — 385 citations
- VD-BERT: A Unified Vision and Dialog Transformer with BERT (2020) — 111 citations
- ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning (2022) — 1,654 citations
- CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation (2021) — 2,385 citations
- Diffusion Model Alignment Using Direct Preference Optimization (2023) — 819 citations
- VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions (2018) — 123 citations
- A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets (2023) — 242 citations
- Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation (2022) — 179 citations
- It’s Morphin’ Time! Combating Linguistic Discrimination with Inflectional Perturbations (2020) — 121 citations
- Is GPT-3 a Good Data Annotator? (2022) — 353 citations
- Unpaired Image Captioning by Language Pivoting (2018) — 89 citations
- A Factorial Deep Markov Model for Unsupervised Disentangled Representation Learning from Speech (2019) — 16 citations
- Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings (2015) — 446 citations
- Distributed Representations of Tuples for Entity Resolution (2017) — 336 citations
- xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval (2023) — 95 citations
- L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models (2023) — 44 citations
- Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation (2022) — 49 citations
- LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5 (2021) — 136 citations