Yizhong Wang
Artificial Intelligence · Annual Meeting of the Association for Computational Linguistics · 2017–2024
A researcher in the Science corpus: 15 papers; trusts 468 researchers and is trusted by 63 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 584 citations into it; #3,556 of 35,345 by trust here, #1,107 by citations
- Natural Language Processing — 306 citations into it; #1,414 of 5,688 by trust here, #627 by citations
- Computer Vision and Pattern Recognition — 257 citations into it; #5,639 of 21,575 by trust here, #2,027 by citations
- Evaluation & Benchmarks — 189 citations into it; #628 of 3,147 by trust here, #430 by citations
- Large Language Models — 131 citations into it; #770 of 799 by trust here, #240 by citations
- Prompting & Reasoning — 70 citations into it
- Representation & Self-Supervised Learning — 42 citations into it
- Information Systems — 35 citations into it
Whom Yizhong Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Alex Graves
- Oriol Vinyals
- Jimmy Ba
Who trusts Yizhong Wang overall
- Swaroop Mishra
- Matt Gardner
- Xiang Yue
- Mor Geva
- Bill Yuchen Lin
- Daniel Khashabi
- Jonathan Berant
- Bo Li
- Eric Wallace
- Sewon Min
Papers from Yizhong Wang's perspective
Ordered by how strongly the researchers Yizhong Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs (2019) — 1,328 citations
- Self-Instruct: Aligning Language Models with Self-Generated Instructions (2022) — 3,444 citations
- TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering (2023) — 442 citations
- Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks (2022) — 1,112 citations
- Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics (2020) — 601 citations
- DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications (2017) — 309 citations
- MultiModalQA: Complex Question Answering over Text, Tables and Images (2021) — 252 citations
- How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources (2023) — 510 citations
- The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus (2021) — 79 citations
- Do NLP Models Know Numbers? Probing Numeracy in Embeddings (2019) — 311 citations
- One Embedder, Any Task: Instruction-Finetuned Text Embeddings (2022) — 475 citations
- OLMo: Accelerating the Science of Language Models (2024) — 700 citations
- Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification (2018) — 125 citations
- TÜLU 3: Pushing Frontiers in Open Language Model Post-Training (2024) — 775 citations
- Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection (2023) — 2,215 citations