Xin Cong

Information Systems · Annual Meeting of the Association for Computational Linguistics · 2023–2024

A researcher in the Science corpus: 5 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Xin Cong trusts overall

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

  1. Youssef Bassil

Papers from Xin Cong's perspective

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

  1. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  2. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  3. Proximal Policy Optimization Algorithms (arXiv.org)
  4. Curriculum learning
  5. MuJoCo: A physics engine for model-based control
  6. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
  7. Chain of Thought Prompting Elicits Reasoning in Large Language Models (Neural Information Processing Systems)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. ImageNet classification with deep convolutional neural networks

Their papers