Papers
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, Jiangtao Wen, Yuxing Han
BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing
Dongliang Guo, Mengxuan Hu, Zihan Guan et al.
Balanced Learning for Domain Adaptive Semantic Segmentation
Wangkai Li, Rui Sun, Bohao Liao et al.
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
Joshua Southern, Yam Eitan, Guy Bar-Shalom et al.
Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
Jin Zhu, Jingyi Li, Hongyi Zhou et al.
Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data
Zhe Zhao, Haibin Wen, Pengkun Wang et al.
Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing
Zhuoying Li, Zhu Xu, Yuxin Peng et al.
Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
Corinna Cortes, Anqi Mao, Mehryar Mohri et al.
BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training
Chenyi Yang, Wenjie Nie, Yuxin Zhang et al.
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
BAnG: Bidirectional Anchored Generation for Conditional RNA Design
Roman Klypa, Alberto Bietti, Sergei Grudinin
Banyan: Improved Representation Learning with Explicit Structure
Mattia Opper, Siddharth N
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
Toby Boyne, Jose Pablo Folch, Robert Matthew Lee et al.
BARNN: A Bayesian Autoregressive and Recurrent Neural Network
Dario Coscia, Max Welling, Nicola Demo et al.
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
Lian Liu, Xiandong Zhao, Guanchen Li et al.
BaxBench: Can LLMs Generate Correct and Secure Backends?
Mark Vero, Niels Mündler, Victor Chibotaru et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.
Bayesian Inference for Correlated Human Experts and Classifiers
Markelle Kelly, Alex James Boyd, Sam Showalter et al.
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
BCE vs. CE in Deep Feature Learning
Qiufu Li, Huibin Xiao, Linlin Shen
BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition
Fei Long, Xiaoou Li, Jiaming Lv et al.