Tao Yu

Artificial Intelligence · with Zhang · 2018–2022

A researcher in the Science corpus: 19 papers; trusts 389 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 664 citations into it; #4,386 of 35,345 by trust here, #1,887 by citations
• Natural Language Processing — 505 citations into it; #1,375 of 5,688 by trust here, #648 by citations
• Computer Vision and Pattern Recognition — 197 citations into it
• Evaluation & Benchmarks — 108 citations into it; #3,113 of 3,147 by trust here, #688 by citations
• Information Systems — 105 citations into it; #2,980 of 8,771 by trust here, #324 by citations
• Representation & Self-Supervised Learning — 44 citations into it
• Management Science and Operations Research — 34 citations into it; #5,327 of 11,946 by trust here, #6,563 by citations
• Model Architectures — 31 citations into it

Whom Tao Yu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Ilya Sutskever
6. Richard Socher
7. Jimmy Ba
8. Oriol Vinyals
9. Percy Liang
10. Yann LeCun

Who trusts Tao Yu overall

1. Rui Zhang
2. Michihiro Yasunaga
3. Ahmed Elgohary
4. Haoyang Li
5. Xinyun Chen
6. Zhuang Li
7. Jiaqi Guo
8. Ben Bogin
9. Jonathan Berant
10. Ruiqi Zhong

Papers from Tao Yu's perspective

Ordered by how strongly the researchers Tao Yu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task (2018) — 1,963 citations
• UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models (2022) — 362 citations
• Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions (2019) — 161 citations
• TypeSQL: Knowledge-Based Type-Aware Neural Text-to-SQL Generation (2018) — 308 citations
• DART: Open-Domain Structured Data Record to Text Generation (2020) — 230 citations
• CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases (2019) — 312 citations
• SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task (2018) — 229 citations
• SParC: Cross-Domain Semantic Parsing in Context (2019) — 251 citations
• QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization (2021) — 488 citations
• DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation (2022) — 563 citations
• Semantic Evaluation for Text-to-SQL with Distilled Test Suite (2020) — 190 citations
• Selective Annotation Makes Language Models Better Few-Shot Learners (2022) — 329 citations
• One Embedder, Any Task: Instruction-Finetuned Text Embeddings (2022) — 475 citations
• ZeroGen: Efficient Zero-shot Learning via Dataset Generation (2022) — 305 citations
• Logic-Consistency Text Generation from Semantic Parses (2021) — 38 citations
• GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing (2020) — 296 citations
• Salvaging Federated Learning by Local Adaptation (2020) — 315 citations
• Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions (2021) — 5 citations
• SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing (2021) — 75 citations