Lidong Bing
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 19 papers; trusts 690 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 548 citations into it; #8,619 of 35,345 by trust here, #3,745 by citations
- Natural Language Processing — 278 citations into it
- Computer Vision and Pattern Recognition — 167 citations into it; #16,826 of 21,575 by trust here, #7,176 by citations
- Large Language Models — 118 citations into it
- Representation & Self-Supervised Learning — 71 citations into it
- Model Architectures — 48 citations into it
- Evaluation & Benchmarks — 45 citations into it
- Information Systems — 43 citations into it; #7,209 of 8,771 by trust here, #2,471 by citations
Whom Lidong Bing trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Richard Socher
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Jimmy Ba
- Yann LeCun
- Alex Graves
Who trusts Lidong Bing overall
Papers from Lidong Bing's perspective
Ordered by how strongly the researchers Lidong Bing 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding (2023) — 1,876 citations
- An Unsupervised Sentence Embedding Method by Mutual Information Maximization (2020) — 197 citations
- Is GPT-3 a Good Data Annotator? (2022) — 353 citations
- On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation (2021) — 255 citations
- LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models (2023) — 497 citations
- Sentiment Analysis in the Era of Large Language Models: A Reality Check (2023) — 629 citations
- On the Effectiveness of Parameter-Efficient Fine-Tuning (2022) — 249 citations
- A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges (2022) — 425 citations
- Exploring Auxiliary Reasoning Tasks for Task-oriented Dialog Systems with Meta Cooperative Learning (2021) — 9 citations
- Aspect Sentiment Quad Prediction as Paraphrase Generation (2021) — 298 citations
- Position-Aware Tagging for Aspect Sentiment Triplet Extraction (2020) — 328 citations
- Review-based Question Generation with Adaptive Instance Transfer and Augmentation (2019) — 20 citations
- Exploiting BERT for End-to-End Aspect-based Sentiment Analysis (2019) — 322 citations
- Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis (2019) — 513 citations
- Transformation Networks for Target-Oriented Sentiment Classification (2018) — 474 citations
- A Unified Model for Opinion Target Extraction and Target Sentiment Prediction (2018) — 354 citations
- Neural Rating Regression with Abstractive Tips Generation for Recommendation (2017) — 338 citations
- Recurrent Attention Network on Memory for Aspect Sentiment Analysis (2017) — 913 citations
- Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists (2015) — 39 citations