Kai Xu - RankMe

32 papers A* 8A 1Journal 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback. CoRR Giorgio Giannone, Anna C. Doris, Amin Heyrani Nobari, Kai Xu, Akash Srivastava, Faez Ahmed
2026	J	`jnl`	S2D2: Fast Decoding for Diffusion LLMs via Training-Free Self-Speculation. CoRR Ligong Han, Hao Wang, Han Gao, Kai Xu, Akash Srivastava
2025	J	`jnl`	A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods. CoRR Isha Puri, Shivchander Sudalairaj, Guangxuan Xu, Kai Xu, Akash Srivastava
2025	J	`jnl`	Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling. CoRR Giorgio Giannone, Guangxuan Xu, Nikhil Shivakumar Nayak, Rohan Mahesh Awhad, Shivchander Sudalairaj, Kai Xu, Akash Srivastava
2025	J	`jnl`	SQuat: Subspace-orthogonal KV Cache Quantization. CoRR Hao Wang, Ligong Han, Kai Xu, Akash Srivastava
2025	J	`jnl`	Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning. CoRR Nikhil Shivakumar Nayak, Krishnateja Killamsetty, Ligong Han, Abhishek Bhandwaldar, Prateek Chanda, Kai Xu, Hao Wang, Aldo Pareja, Oleg Silkin, Mustafa Eyceoz, Akash Srivastava
2025	J	`jnl`	Token-Level Uncertainty Estimation for Large Language Model Reasoning. CoRR Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris N. Metaxas, Hao Wang
2025	A*	`conf`	Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. ICLR Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2024	J	`jnl`	CDR: Customizable Density Ratios of Strong-over-weak LLMs for Preference Annotation. CoRR Guangxuan Xu, Kai Xu, Shivchander Sudalairaj, Hao Wang, Akash Srivastava
2024	J	`jnl`	LAB: Large-Scale Alignment for ChatBots. CoRR Shivchander Sudalairaj, Abhishek Bhandwaldar, Aldo Pareja, Kai Xu, David D. Cox, Akash Srivastava
2024	J	`jnl`	LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis. CoRR Amin Heyrani Nobari, Akash Srivastava, Dan Gutfreund, Kai Xu, Faez Ahmed
2024	J	`jnl`	LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis. Trans. Mach. Learn. Res. Amin Heyrani Nobari, Akash Srivastava, Dan Gutfreund, Kai Xu, Faez Ahmed
2024	J	`jnl`	Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. CoRR Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2024	J	`jnl`	Urban context and delivery performance: Modelling service time for cargo bikes and vans across diverse urban environments. CoRR Maxwell Schrader, Navish Kumar, Esben Sørig, Soonmyeong Yoon, Akash Srivastava, Kai Xu, Maria Sinziana Astefanoaei, Nicolas Collignon
2023	J	`jnl`	Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression. CoRR Akash Srivastava, Seungwook Han, Kai Xu, Benjamin Rhodes, Michael U. Gutmann
2023	J	`jnl`	Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression. Trans. Mach. Learn. Res. Akash Srivastava, Seungwook Han, Kai Xu, Benjamin Rhodes, Michael U. Gutmann
2023	J	`jnl`	Modelling the performance of delivery vehicles across urban micro-regions to accelerate the transition to cargo-bike logistics. CoRR Max Schrader, Navish Kumar, Nicolas Collignon, Esben Sørig, Soonmyeong Yoon, Akash Srivastava, Kai Xu, Maria Sinziana Astefanoaei
2023	A*	`conf`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. ICML Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2023	J	`jnl`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. CoRR Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2022	J	`jnl`	Repairing Systematic Outliers by Learning Clean Subspaces in VAEs. CoRR Simão Eduardo, Kai Xu, Alfredo Nazábal, Charles Sutton
2021	A*	`conf`	A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. NeurIPS Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer D. Ullman, Josh Tenenbaum, Charles Sutton
2021	A	`conf`	Couplings for Multinomial Hamiltonian Monte Carlo. AISTATS Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge
2021	A*	`conf`	Targeted Neural Dynamical Modeling. NeurIPS Cole L. Hurwitz, Akash Srivastava, Kai Xu, Justin Jude, Matthew G. Perich, Lee E. Miller, Matthias H. Hennig
2020	A*	`conf`	Generative Ratio Matching Networks. ICLR Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton
2020	J	`jnl`	Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling. CoRR Akash Srivastava, Yamini Bansal, Yukun Ding, Cole L. Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund
2020	A*	`conf`	Telescoping Density-Ratio Estimation. NeurIPS Benjamin Rhodes, Kai Xu, Michael U. Gutmann
2020	J	`jnl`	Telescoping Density-Ratio Estimation. CoRR Benjamin Rhodes, Kai Xu, Michael U. Gutmann
2019	A*	`conf`	Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference. NeurIPS Cole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino, Matthias H. Hennig
2019	J	`jnl`	Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference. CoRR Cole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino, Matthias H. Hennig
2019	A*	`conf`	Variational Russian Roulette for Deep Bayesian Nonparametrics. ICML Kai Xu, Akash Srivastava, Charles Sutton
2018	J	`jnl`	Interpreting Deep Classifier by Visual Distillation of Dark Knowledge. CoRR Kai Xu, Dae Hoon Park, Chang Yi, Charles Sutton
2018	J	`jnl`	Ratio Matching MMD Nets: Low dimensional projections for effective deep generative models. CoRR Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton