Ximing Lu
Artificial Intelligence · 2020–2023
A researcher in the Science corpus: 18 papers; trusts 916 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 664 citations into it; #15,566 of 35,345 by trust here, #4,888 by citations
- Natural Language Processing — 406 citations into it; #2,351 of 5,688 by trust here, #845 by citations
- Computer Vision and Pattern Recognition — 335 citations into it; #18,825 of 21,575 by trust here, #5,161 by citations
- Large Language Models — 165 citations into it
- Evaluation & Benchmarks — 111 citations into it
- Multimodal Learning — 89 citations into it
- Safety, Robustness & Interpretability — 86 citations into it; #2,250 of 2,251 by trust here, #1,290 by citations
- Prompting & Reasoning — 78 citations into it
Whom Ximing Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Kaiming He
- Alex Krizhevsky
- Ilya Sutskever
- Alec Radford
- Yann LeCun
- Richard Socher
- Alex Graves
Who trusts Ximing Lu overall
- Sachin Kumar
- Sean Welleck
- Yulia Tsvetkov
- Jiacheng Liu
- Mengyao Cao
- Biswajit Paria
- Vidhisha Balachandran
- Yi Wang
- Jaehun Jung
- Aman Madaan
Papers from Ximing Lu's perspective
Ordered by how strongly the researchers Ximing Lu 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
- MERLOT: Multimodal Neural Script Knowledge Models (2021) — 455 citations
- DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts (2021) — 533 citations
- Symbolic Knowledge Distillation: from General Language Models to Commonsense Models (2021) — 392 citations
- Quark: Controllable Text Generation with Reinforced Unlearning (2022) — 277 citations
- NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints (2020) — 177 citations
- Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models (2020) — 14 citations
- NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics (2021) — 200 citations
- The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning (2023) — 325 citations
- NaturalProver: Grounded Mathematical Proof Generation with Language Models (2022) — 105 citations
- Faith and Fate: Limits of Transformers on Compositionality (2023) — 650 citations
- Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model (2023) — 39 citations
- ProsocialDialog: A Prosocial Backbone for Conversational Agents (2022) — 159 citations
- MERLOT RESERVE: Neural Script Knowledge through Vision and Language and Sound (2022) — 261 citations
- Generating Sequences by Learning to Self-Correct (2022) — 352 citations
- Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering (2022) — 64 citations
- Generated Knowledge Prompting for Commonsense Reasoning (2021) — 407 citations
- Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer (2021) — 30 citations
- On-the-Fly Controlled Text Generation with Experts and Anti-Experts (2021) — 16 citations