Kai Sheng Tai - RankMe

21 papers A* 4Journal 12Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	MobileLLM-Pro Technical Report. CoRR Patrick Huber, Ernie Chang, Wei Wen, Igor Fedorov, Tarek Elgamal, Hanxian Huang, Naveen Suda, Chinnadhurai Sankar, Vish Vogeti, Yanghan Wang, Alex Gladkov, Kai Sheng Tai, Abdelrahman Elogeel, Tarek Hefny, Vikas Chandra, Ahmed Aly, Anuj Kumar, Raghuraman Krishnamoorthi, Adithya Sagar
2025	—	`conf`	Multi-entity Video Transformers for Fine-Grained Video Representation Learning. CVPR Workshops Matthew Walmer, Rose Catherine Kanjirathinkal, Kai Sheng Tai, Keyur Muzumdar, Tai-Peng Tian, Abhinav Shrivastava
2025	J	`jnl`	The Path Not Taken: RLVR Provably Learns Off the Principals. CoRR Hanqing Zhu, Zhenyu Zhang, Hanxian Huang, DiJia Su, Zechun Liu, Jiawei Zhao, Igor Fedorov, Hamed Pirsiavash, Zhizhou Sha, Jinwon Lee, David Z. Pan, Zhangyang Wang, Yuandong Tian, Kai Sheng Tai
2024	—	`conf`	uCAP: An Unsupervised Prompting Method for Vision-Language Models. ECCV (74) A. Tuan Nguyen, Kai Sheng Tai, Bor-Chun Chen, Satya Narayan Shukla, Hanchao Yu, Philip Torr, Tai-Peng Tian, Ser-Nam Lim
2023	J	`jnl`	Analyzing Populations of Neural Networks via Dynamical Model Embedding. CoRR Jordan Cotler, Kai Sheng Tai, Felipe Hernández, Blake Elias, David Sussillo
2023	J	`jnl`	Multi-entity Video Transformers for Fine-Grained Video Representation Learning. CoRR Matthew Walmer, Rose Catherine Kanjirathinkal, Kai Sheng Tai, Keyur Muzumdar, Tai-Peng Tian, Abhinav Shrivastava
2022	A*	`conf`	Spartan: Differentiable Sparsity via Regularized Transportation. NeurIPS Kai Sheng Tai, Tai-Peng Tian, Ser Nam Lim
2022	J	`jnl`	Spartan: Differentiable Sparsity via Regularized Transportation. CoRR Kai Sheng Tai, Tai-Peng Tian, Ser-Nam Lim
2021	A*	`conf`	Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training. ICML Kai Sheng Tai, Peter Bailis, Gregory Valiant
2021	J	`jnl`	Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training. CoRR Kai Sheng Tai, Peter Bailis, Gregory Valiant
2021	—	`—`	Statistical learning under resource constraints. Kai Sheng Tai
2019	A*	`conf`	Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data. ICML Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant
2019	A*	`conf`	Equivariant Transformer Networks. ICML Kai Sheng Tai, Peter Bailis, Gregory Valiant
2019	J	`jnl`	Equivariant Transformer Networks. CoRR Kai Sheng Tai, Peter Bailis, Gregory Valiant
2018	J	`jnl`	Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. CoRR Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis
2018	J	`jnl`	Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. Proc. VLDB Endow. Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis
2018	—	`conf`	Sketching Linear Classifiers over Data Streams. SIGMOD Conference Kai Sheng Tai, Vatsal Sharan, Peter Bailis, Gregory Valiant
2017	J	`jnl`	Finding Heavily-Weighted Features in Data Streams. CoRR Kai Sheng Tai, Vatsal Sharan, Peter Bailis, Gregory Valiant
2017	J	`jnl`	There and Back Again: A General Approach to Learning Sparse Models. CoRR Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant
2015	—	`conf`	Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks. ACL (1) Kai Sheng Tai, Richard Socher, Christopher D. Manning
2015	J	`jnl`	Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks. CoRR Kai Sheng Tai, Richard Socher, Christopher D. Manning