Tiancheng Zhao

Artificial Intelligence · 2016–2025

A researcher in the Science corpus: 8 papers; trusts 376 researchers and is trusted by 95 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 177 citations into it; #2,576 of 35,345 by trust here, #4,956 by citations
• Natural Language Processing — 120 citations into it; #751 of 5,688 by trust here, #1,240 by citations
• Computer Vision and Pattern Recognition — 58 citations into it; #9,164 of 21,575 by trust here, #11,498 by citations
• Evaluation & Benchmarks — 30 citations into it
• Reinforcement Learning — 29 citations into it; #454 of 2,242 by trust here, #1,055 by citations
• Information Retrieval & Search — 25 citations into it; #691 of 1,022 by trust here, #771 by citations
• Large Language Models — 17 citations into it
• Model Architectures — 15 citations into it

Whom Tiancheng Zhao trusts overall

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

1. Diederik P. Kingma
2. Ilya Sutskever
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Oriol Vinyals
6. Sepp Hochreiter
7. Alex Krizhevsky
8. Ronald J. Williams
9. Jason Williams
10. Alex Graves

Who trusts Tiancheng Zhao overall

1. Jianfeng Gao
2. Paweł Budzianowski
3. Chunyuan Li
4. Weikang Wang
5. Bing Liu
6. Maxine Eskénazi
7. Shikib Mehri
8. Thibault Formal
9. Bhuwan Dhingra
10. Chien-Sheng Wu

Papers from Tiancheng Zhao's perspective

Ordered by how strongly the researchers Tiancheng Zhao 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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

• Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders (2017) — 786 citations
• Towards End-to-End Learning for Dialog State Tracking and Management using Deep Reinforcement Learning (2016) — 277 citations
• Generative Encoder-Decoder Models for Task-Oriented Spoken Dialog Systems with Chatting Capability (2017) — 89 citations
• Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models (2019) — 148 citations
• Beyond Turing: Intelligent Agents Centered on the User (2019) — 13 citations
• SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer Matching Retrieval (2020) — 110 citations
• VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model (2025) — 492 citations
• DialCrowd: A toolkit for easy dialog system assessment (2018) — 16 citations