Baolin Peng

Artificial Intelligence · 2014–2023

A researcher in the Science corpus: 17 papers; trusts 431 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 413 citations into it; #5,436 of 35,345 by trust here, #2,711 by citations
• Natural Language Processing — 277 citations into it; #2,118 of 5,688 by trust here, #1,571 by citations
• Computer Vision and Pattern Recognition — 133 citations into it; #18,148 of 21,575 by trust here, #6,089 by citations
• Large Language Models — 94 citations into it
• Evaluation & Benchmarks — 60 citations into it
• Reinforcement Learning — 46 citations into it
• Model Architectures — 38 citations into it
• Representation & Self-Supervised Learning — 29 citations into it

Whom Baolin Peng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Graves
5. Ilya Sutskever
6. Alex Krizhevsky
7. Ronald J. Williams
8. Yann LeCun
9. Tomas Mikolov
10. Jason Aaron Edward Weston

Who trusts Baolin Peng overall

1. Andrea Madotto
2. Mihir Kale
3. Chunyuan Li
4. Bing Liu
5. Jianfeng Gao
6. Chia-Hsuan Lee
7. Caiming Xiong
8. Arvind Neelakantan
9. Yilin Shen
10. Zhaojiang Lin

Papers from Baolin Peng's perspective

Ordered by how strongly the researchers Baolin Peng trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Instruction Tuning with GPT-4 (2023) — 837 citations
• Towards Neural Network-based Reasoning (2015) — 75 citations
• Attention with Intention for a Neural Network Conversation Model (2015) — 115 citations
• Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback (2023) — 530 citations
• Spoken language understanding using long short-term memory neural networks (2014) — 308 citations
• Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models (2023) — 483 citations
• SOLOIST: Few-shot Task-Oriented Dialog with A Single Pre-trained Auto-regressive Model (2020) — 126 citations
• Few-shot Natural Language Generation for Task-Oriented Dialog (2020) — 210 citations
• Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning (2017) — 195 citations
• Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space (2020) — 202 citations
• GODEL: Large-Scale Pre-Training for Goal-Directed Dialog (2022) — 80 citations
• Few-Shot Named Entity Recognition: A Comprehensive Study (2020) — 83 citations
• ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems (2020) — 118 citations
• Meta Dialogue Policy Learning (2020) — 8 citations
• Task-oriented Dialogue System for Automatic Diagnosis (2018) — 245 citations
• An Attentional Neural Conversation Model with Improved Specificity (2016) — 31 citations
• Recurrent Neural Networks with External Memory for Spoken Language Understanding (2015) — 49 citations