Lichang Chen

Artificial Intelligence · 2023–2024

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 85 citations into it
• Reinforcement Learning — 8 citations into it

Whom Lichang Chen trusts overall

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

1. Ronald J. Williams
2. Diederik P. Kingma
3. John Schulman
4. Geoffrey E. Hinton
5. Tim Salimans
6. Yoshua Bengio
7. Alex Krizhevsky
8. Kaiming He
9. Ilya Sutskever
10. Yann LeCun

Papers from Lichang Chen's perspective

Ordered by how strongly the researchers Lichang Chen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Hallusionbench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models (2023) — 618 citations
• ODIN: Disentangled Reward Mitigates Hacking in RLHF (2024) — 129 citations
• From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning (2023) — 373 citations