Xuankai Chang
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 10 papers; trusts 99 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 287 citations into it
- Signal Processing — 223 citations into it
- Speech & Audio — 168 citations into it
- Natural Language Processing — 69 citations into it
- Computer Vision and Pattern Recognition — 59 citations into it
- Large Language Models — 41 citations into it
- Model Architectures — 38 citations into it
- Representation & Self-Supervised Learning — 35 citations into it
Whom Xuankai Chang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dong Yu
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Graves
- Diederik P. Kingma
- Yi Luo
- Oriol Vinyals
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
Who trusts Xuankai Chang overall
Papers from Xuankai Chang's perspective
Ordered by how strongly the researchers Xuankai Chang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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)
- 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)
Their papers
- Recent Developments on Espnet Toolkit Boosted By Conformer (2020) — 292 citations
- SUPERB: Speech processing Universal PERformance Benchmark (2021) — 1,225 citations
- AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head (2023) — 405 citations
- Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals (2020) — 27 citations
- Discretization and Re-synthesis: an alternative method to solve the Cocktail Party Problem (2021) — 22 citations
- SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities (2022) — 133 citations
- UniAudio: An Audio Foundation Model Toward Universal Audio Generation (2023) — 215 citations
- VoxtLM: Unified Decoder-Only Models for Consolidating Speech Recognition, Synthesis and Speech, Text Continuation Tasks (2023) — 99 citations
- TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition (2023) — 18 citations
- Single-Channel Multi-talker Speech Recognition with Permutation Invariant Training (2017) — 87 citations