Xin Li

Artificial Intelligence · Conference on Empirical Methods in Natural Language Processing · 2018–2025

A researcher in the Science corpus: 10 papers; trusts 354 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 346 citations into it; #16,854 of 35,345 by trust here, #7,471 by citations
• Computer Vision and Pattern Recognition — 205 citations into it; #16,832 of 21,575 by trust here, #7,340 by citations
• Natural Language Processing — 100 citations into it
• Large Language Models — 88 citations into it
• Multimodal Learning — 78 citations into it
• Representation & Self-Supervised Learning — 29 citations into it
• Model Architectures — 27 citations into it
• Optimization & Training — 7 citations into it

Whom Xin Li trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Kaiming He
5. Jimmy Ba
6. Ilya Sutskever
7. Yoon Kim
8. Alex Krizhevsky
9. Richard Socher
10. Yann LeCun

Who trusts Xin Li overall

1. Wenxuan Zhang
2. Lidong Bing
3. Mayur Wankhade
4. Chen Zhang
5. Hanjie Chen
6. Lu Xu
7. Hao Tang
8. Yujia Xiao
9. Yang Deng
10. Haiyun Peng

Papers from Xin Li's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. 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
• VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding (2025) — 513 citations
• VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs (2024) — 817 citations
• Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding (2023) — 737 citations
• SeaLLMs - Large Language Models for Southeast Asia (2023) — 146 citations
• A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges (2022) — 425 citations
• Aspect Sentiment Quad Prediction as Paraphrase Generation (2021) — 298 citations
• Exploiting BERT for End-to-End Aspect-based Sentiment Analysis (2019) — 322 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