Wenhan Xiong
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 15 papers; trusts 597 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 429 citations into it; #6,380 of 35,345 by trust here, #2,465 by citations
- Natural Language Processing — 278 citations into it; #2,275 of 5,688 by trust here, #1,078 by citations
- Computer Vision and Pattern Recognition — 202 citations into it; #6,892 of 21,575 by trust here, #4,105 by citations
- Information Retrieval & Search — 103 citations into it
- Evaluation & Benchmarks — 92 citations into it
- Large Language Models — 77 citations into it
- Information Systems — 59 citations into it
- Model Architectures — 51 citations into it
Whom Wenhan Xiong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Jimmy Ba
- Kaiming He
- Yann LeCun
- Alex Graves
- Richard Socher
Who trusts Wenhan Xiong overall
- Hongyu Ren
- Boshi Wang
- Yi Tay
- Chenguang Zhu
- Ruiyang Ren
- Sewon Min
- Nora Kassner
- Wayne Xin Zhao
- Ivana Balazevic
- Komal K. Teru
Papers from Wenhan Xiong's perspective
Ordered by how strongly the researchers Wenhan Xiong 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation (2018) — 225 citations
- HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data (2020) — 415 citations
- Code Llama: Open Foundation Models for Code (2023) — 3,394 citations
- Do Multi-hop Readers Dream of Reasoning Chains? (2019) — 27 citations
- SCROLLS: Standardized CompaRison Over Long Language Sequences (2022) — 184 citations
- Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader (2019) — 126 citations
- DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning (2017) — 867 citations
- Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model (2019) — 216 citations
- Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval (2020) — 246 citations
- Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering (2019) — 11 citations
- Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering (2020) — 18 citations
- TWEETQA: A Social Media Focused Question Answering Dataset (2019) — 87 citations
- Sentence Embedding Alignment for Lifelong Relation Extraction (2019) — 173 citations
- Effective Long-Context Scaling of Foundation Models (2023) — 346 citations
- Boosted Dense Retriever (2021) — 18 citations