Lingming Zhang

Information Systems · 2018–2024

A researcher in the Science corpus: 9 papers; trusts 239 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 162 citations into it; #1,745 of 8,771 by trust here, #2,145 by citations
• Software — 148 citations into it; #233 of 1,227 by trust here, #250 by citations
• Artificial Intelligence — 139 citations into it
• Natural Language Processing — 90 citations into it
• Large Language Models — 65 citations into it
• Code Generation & Program Synthesis — 45 citations into it
• Evaluation & Benchmarks — 33 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it

Whom Lingming Zhang trusts overall

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

1. Ilya Sutskever
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Oriol Vinyals
7. Radford M. Neal
8. David E. Rumelhart
9. Yann LeCun
10. Chun Xia

Who trusts Lingming Zhang overall

1. Chun Xia
2. Yinlin Deng
3. Jiawei Liu
4. Soren Dunn
5. Haoran Peng
6. Angela Fan
7. Terry Yue Zhuo

Papers from Lingming Zhang's perspective

Ordered by how strongly the researchers Lingming Zhang 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Agentless: Demystifying LLM-based Software Engineering Agents (2024) — 421 citations
• Fuzz4ALL: Universal Fuzzing with Large Language Models (2023) — 326 citations
• Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation (2023) — 1,966 citations
• Automated Program Repair via Conversation: Fixing 162 out of 337 Bugs for $0.42 Each using ChatGPT (2023) — 348 citations
• Automated Program Repair in the Era of Large Pre-trained Language Models (2022) — 380 citations
• Large Language Models Are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models (2022) — 383 citations
• Less training, more repairing please: revisiting automated program repair via zero-shot learning (2022) — 298 citations
• DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization (2019) — 341 citations
• DeepRoad: GAN-Based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems (2018) — 648 citations