Qian Liu
Artificial Intelligence · arXiv.org · 2020–2024
A researcher in the Science corpus: 13 papers; trusts 286 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 418 citations into it; #31,629 of 35,345 by trust here, #5,565 by citations
- Natural Language Processing — 266 citations into it; #5,094 of 5,688 by trust here, #2,695 by citations
- Computer Vision and Pattern Recognition — 127 citations into it
- Large Language Models — 127 citations into it
- Evaluation & Benchmarks — 69 citations into it
- Model Architectures — 36 citations into it
- Code Generation & Program Synthesis — 29 citations into it
- Signal Processing — 22 citations into it
Whom Qian Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Ronald J. Williams
- Oriol Vinyals
- Yann LeCun
- Dzmitry Bahdanau
- Kaiming He
Who trusts Qian Liu overall
- Wenhu Chen
- Pan Lu
- Bing Liu
- Jorge Armando Mendez Mendez
- Tianbao Xie
- Peter Shaw
- Ansong Ni
- Jinhao Jiang
- Xinyu Pi
- Zhoujun Cheng
Papers from Qian Liu's perspective
Ordered by how strongly the researchers Qian Liu 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
- SantaCoder: don't reach for the stars! (2023) — 247 citations
- TAPEX: Table Pre-training via Learning a Neural SQL Executor (2021) — 368 citations
- StarCoder: may the source be with you! (2023) — 1,263 citations
- Benchmarking Meaning Representations in Neural Semantic Parsing (2020) — 29 citations
- Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models (2022) — 47 citations
- Bag of Tricks for Training Data Extraction from Language Models (2023) — 95 citations
- Active Retrieval Augmented Generation (2023) — 758 citations
- You Impress Me: Dialogue Generation via Mutual Persona Perception (2020) — 187 citations
- StarCoder 2 and The Stack v2: The Next Generation (2024) — 698 citations
- LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition (2023) — 393 citations
- Reasoning Like Program Executors (2022) — 61 citations
- ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question Answering (2021) — 83 citations
- Compositional Generalization by Learning Analytical Expressions (2020) — 78 citations