Albert Qiaochu Jiang
Artificial Intelligence · 2020–2024
A researcher in the Science corpus: 8 papers; trusts 42 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 201 citations into it; #18,667 of 35,345 by trust here, #3,937 by citations
- Large Language Models — 64 citations into it
- Natural Language Processing — 60 citations into it; #4,266 of 5,688 by trust here, #1,377 by citations
- Prompting & Reasoning — 54 citations into it; #349 of 359 by trust here, #289 by citations
- Computer Vision and Pattern Recognition — 43 citations into it
- Computational Theory and Mathematics — 32 citations into it
- Information Systems — 30 citations into it; #8,664 of 8,771 by trust here, #2,307 by citations
- Model Architectures — 20 citations into it
Whom Albert Qiaochu Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Stanislas Polu
- Geoffrey E. Hinton
- Diederik P. Kingma
- Christian Szegedy
- Yoshua Bengio
- Alex Krizhevsky
- Jesse Michael Han
- Lawrence Charles Paulson
- Kaiming He
Who trusts Albert Qiaochu Jiang overall
- Zhangir Azerbayev
- Emily First
- Michael R Douglas
- Markus Norman Rabe
- Hong-Liu Cao
- Hailey Schoelkopf
- Yuhuai Wu
- Zhihong Shao
- Sean Welleck
- Pan Lu
Papers from Albert Qiaochu Jiang's perspective
Ordered by how strongly the researchers Albert Qiaochu Jiang 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)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Mistral 7B (2023) — 3,685 citations
- Autoformalization with Large Language Models (2022) — 324 citations
- Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers (2022) — 144 citations
- INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving (2020) — 60 citations
- Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs (2022) — 338 citations
- Mixtral of Experts (2024) — 2,015 citations
- Evaluating Language Models for Mathematics through Interactions (2023) — 114 citations
- Llemma: An Open Language Model For Mathematics (2023) — 478 citations