Papers
Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere et al.
Better Locally Private Sparse Estimation Given Multiple Samples Per User
Yuheng Ma, Ke Jia, Hanfang Yang
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
BetterV: Controlled Verilog Generation with Discriminative Guidance
Zehua Pei, Huiling Zhen, Mingxuan Yuan et al.
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Nikhil Sardana, Jacob Portes, Sasha Doubov et al.
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
Denis Blessing, Xiaogang Jia, Johannes Esslinger et al.
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
Hugo Thimonier, Fabrice Popineau, Arpad Rimmel et al.
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
Levi E. Lingsch, Mike Yan Michelis, Emmanuel De Bezenac et al.
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja Balle et al.
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
Mengmeng Ma, Tang Li, Xi Peng
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets
Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
Zhiyuan He, Yijun Yang, Pin-Yu Chen et al.
Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
Yuanwei Liu, Junwei Han, Xiwen Yao et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Bifurcated Attention for Single-Context Large-Batch Sampling
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda et al.
Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering
Mitchell Black, Lucy Lin, Weng-Keen Wong et al.
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Wei Huang, Yangdong Liu, Haotong Qin et al.
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
Jun-Yi Hang, Min-Ling Zhang
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hyeseung Cho et al.
Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani