Yujia Qin
Artificial Intelligence · 2019–2025
A researcher in the Science corpus: 17 papers; trusts 164 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 540 citations into it
- Natural Language Processing — 243 citations into it
- Computer Vision and Pattern Recognition — 227 citations into it
- Large Language Models — 219 citations into it
- Evaluation & Benchmarks — 57 citations into it
- Representation & Self-Supervised Learning — 57 citations into it
- Reinforcement Learning — 37 citations into it
- Optimization & Training — 32 citations into it
Whom Yujia Qin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Alec Radford
- Yann LeCun
- Jimmy Ba
- Alex Graves
Who trusts Yujia Qin overall
- Yusheng Su
- Tara Safavi
- Xingyao Wang
- Ning Ding
- Tianxiang Sun
- Yankai Lin
- Qinyuan Ye
- Qiusi Zhan
- Sabeen Ahmed
- Jian Xie
Papers from Yujia Qin's perspective
Ordered by how strongly the researchers Yujia Qin trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs (2023) — 1,907 citations
- Learning from Explanations with Neural Execution Tree (2019) — 41 citations
- CPM: A Large-scale Generative Chinese Pre-trained Language Model (2020) — 132 citations
- bert2BERT: Towards Reusable Pretrained Language Models (2021) — 87 citations
- UI-TARS: Pioneering Automated GUI Interaction with Native Agents (2025) — 510 citations
- Seed1.5-VL Technical Report (2025) — 350 citations
- RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation (2024) — 102 citations
- Tool Learning with Foundation Models (2023) — 420 citations
- Parameter-efficient fine-tuning of large-scale pre-trained language models (2023) — 1,192 citations
- Enhancing Chat Language Models by Scaling High-quality Instructional Conversations (2023) — 944 citations
- AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents (2023) — 698 citations
- ELLE: Efficient Lifelong Pre-training for Emerging Data (2022) — 92 citations
- On Transferability of Prompt Tuning for Natural Language Understanding (2021) — 21 citations
- Knowledge Inheritance for Pre-trained Language Models (2021) — 65 citations
- Exploring Low-dimensional Intrinsic Task Subspace via Prompt Tuning (2021) — 39 citations
- ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning (2020) — 143 citations
- Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations (2019)