Genta Indra Winata
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 15 papers; trusts 224 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 517 citations into it; #24,735 of 35,345 by trust here, #9,557 by citations
- Natural Language Processing — 411 citations into it
- Computer Vision and Pattern Recognition — 149 citations into it
- Large Language Models — 132 citations into it
- Evaluation & Benchmarks — 110 citations into it
- Representation & Self-Supervised Learning — 47 citations into it
- General Social Sciences — 18 citations into it
- Optimization & Training — 12 citations into it
Whom Genta Indra Winata trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Alexis Conneau
- Yann LeCun
- Richard Socher
- Kaiming He
- Alex Graves
Who trusts Genta Indra Winata overall
Papers from Genta Indra Winata's perspective
Ordered by how strongly the researchers Genta Indra Winata trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
Their papers
- Language Models are Few-shot Multilingual Learners (2021) — 173 citations
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code (2022) — 43 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding (2020) — 491 citations
- Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables (2019) — 71 citations
- BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling (2021) — 68 citations
- Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual Learning (2020) — 20 citations
- MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems (2020) — 183 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting (2022) — 114 citations
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapters (2021) — 47 citations
- Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems (2020) — 72 citations
- Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring (2019) — 21 citations