Changsong Liu

Artificial Intelligence · 2014–2017

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #22,236 of 35,345 by trust here, #21,878 by citations
• Natural Language Processing — 14 citations into it; #4,240 of 5,688 by trust here, #4,879 by citations
• Multimodal Learning — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it; #16,061 of 21,575 by trust here, #20,271 by citations
• Reinforcement Learning — 5 citations into it; #1,759 of 2,242 by trust here, #2,160 by citations

Whom Changsong Liu trusts overall

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

1. Jayant Krishnamurthy
2. Terry Regier
3. Joyce Yue Chai
4. Raymond J. Mooney
5. Thomas Kollar
6. Lanbo She
7. Laura A. Carlson
8. Johannes Pittermann
9. Stephen W. Carden
10. David L. Chen

Who trusts Changsong Liu overall

1. Joyce Yue Chai
2. Rui Fang
3. Leah Perlmutter
4. Qiaozi Gao

Papers from Changsong Liu's perspective

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

1. Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation
2. ImageNet classification with deep convolutional neural networks
3. Learning to Interpret Natural Language Navigation Instructions from Observations
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. A Joint Model of Language and Perception for Grounded Attribute Learning
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World

Their papers

• Collaborative Language Grounding Toward Situated Human-Robot Dialogue (2017) — 52 citations
• Learning to Mediate Perceptual Differences in Situated Human-Robot Dialogue (2015) — 21 citations
• Collaborative Effort towards Common Ground in Situated Human-Robot Dialogue (2014) — 106 citations