Jing Xu

Artificial Intelligence · with Weston · 2020–2024

A researcher in the Science corpus: 11 papers; trusts 270 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 354 citations into it; #4,314 of 35,345 by trust here, #2,484 by citations
• Natural Language Processing — 282 citations into it; #1,499 of 5,688 by trust here, #836 by citations
• Computer Vision and Pattern Recognition — 82 citations into it; #7,791 of 21,575 by trust here, #3,747 by citations
• Safety, Robustness & Interpretability — 79 citations into it; #703 of 2,251 by trust here, #557 by citations
• Large Language Models — 73 citations into it
• Evaluation & Benchmarks — 52 citations into it
• Information Systems — 47 citations into it
• Social Psychology — 19 citations into it

Whom Jing Xu trusts overall

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

1. Jason Aaron Edward Weston
2. Emily Dinan
3. Kurt Shuster
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Stephen Roller
7. Diederik P. Kingma
8. Ilya Sutskever
9. Alex Krizhevsky
10. Kaiming He

Who trusts Jing Xu overall

1. Eric Michael Smith
2. Kurt Shuster
3. Emily Dinan
4. Weiyan Shi
5. Jason Aaron Edward Weston
6. Dian Yu
7. Mojtaba Komeili
8. Nicholas Meade
9. Hao Sun
10. Kushal Arora

Papers from Jing Xu's perspective

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

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

Their papers

• Recipes for Building an Open-Domain Chatbot (2020) — 1,145 citations
• Recipes for Safety in Open-domain Chatbots (2020) — 257 citations
• Bot-Adversarial Dialogue for Safe Conversational Agents (2021) — 179 citations
• When Life Gives You Lemons, Make Cherryade: Converting Feedback from Bad Responses into Good Labels (2022) — 23 citations
• BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage (2022) — 297 citations
• Beyond Goldfish Memory: Long-Term Open-Domain Conversation (2021) — 363 citations
• Learning New Skills after Deployment: Improving open-domain internet-driven dialogue with human feedback (2022) — 47 citations
• SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures (2021) — 55 citations
• Chain-of-Verification Reduces Hallucination in Large Language Models (2023) — 515 citations
• Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls (2022) — 19 citations
• Self-Rewarding Language Models (2024) — 663 citations