Chuanqi Tan
Artificial Intelligence · with Zhou · 2014–2023
A researcher in the Science corpus: 13 papers; trusts 186 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 495 citations into it; #11,707 of 35,345 by trust here, #2,975 by citations
- Natural Language Processing — 229 citations into it; #3,455 of 5,688 by trust here, #1,837 by citations
- Large Language Models — 187 citations into it
- Computer Vision and Pattern Recognition — 154 citations into it
- Prompting & Reasoning — 133 citations into it
- Evaluation & Benchmarks — 61 citations into it
- Optimization & Training — 25 citations into it
- Model Architectures — 21 citations into it
Whom Chuanqi Tan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Oriol Vinyals
- Ilya Sutskever
- Alex Krizhevsky
- Richard Socher
- Matthew D. Zeiler
- Yann LeCun
- Christopher D. Manning
Who trusts Chuanqi Tan overall
- Rajarshee Mitra
- Duyu Tang
- Bin Bi
- Arun Tejasvi Chaganty
- Duy-Tin Vo
- Linfeng Song
- Minghao Hu
- Kyosuke Nishida
- Yizhong Wang
- Xiaoya Li
Papers from Chuanqi Tan's perspective
Ordered by how strongly the researchers Chuanqi Tan 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- Neural Question Generation from Text: A Preliminary Study (2017) — 370 citations
- S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension (2017) — 92 citations
- Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners (2021) — 209 citations
- RRHF: Rank Responses to Align Language Models with Human Feedback without tears (2023) — 545 citations
- Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023) — 354 citations
- Qwen Technical Report (2023) — 4,095 citations
- Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification (2014) — 984 citations
- Reasoning with Language Model Prompting: A Survey (2022) — 441 citations
- KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction (2021) — 507 citations
- I Know There Is No Answer: Modeling Answer Validation for Machine Reading Comprehension (2018) — 29 citations
- AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction (2021)
- Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning (2021) — 228 citations
- SuperAgent: A Customer Service Chatbot for E-commerce Websites (2017) — 320 citations