Papers
11,015 papers found
Binding Language Models in Symbolic Languages
Zhoujun Cheng, Tianbao Xie, Peng Shi et al.
Bispectral Neural Networks
Sophia Sanborn, Christian A Shewmake, Bruno Olshausen et al.
Bit-Pruning: A Sparse Multiplication-Less Dot-Product
Yusuke Sekikawa, Shingo Yashima
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Amrith Setlur, Don Dennis, Benjamin Eysenbach et al.
Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
Yun-Chen Lo, Tse-Kuang Lee, Ren-Shuo Liu
Blurring Diffusion Models
Emiel Hoogeboom, Tim Salimans
Boosting Adversarial Transferability using Dynamic Cues
Muzammal Naseer, Ahmad Mahmood, Salman Khan et al.
Boosting Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma et al.
Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
Jianye HAO, Xiaotian Hao, Hangyu Mao et al.
Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
Yinan Huang, Xingang Peng, Jianzhu Ma et al.
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
Borui Zhang, Wenzhao Zheng, Jie Zhou et al.
BrainBERT: Self-supervised representation learning for intracranial recordings
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari et al.
Brain-like representational straightening of natural movies in robust feedforward neural networks
Tahereh Toosi, Elias Issa
Breaking Correlation Shift via Conditional Invariant Regularizer
Mingyang Yi, Ruoyu Wang, Jiacheng Sun et al.
Bridge the Inference Gaps of Neural Processes via Expectation Maximization
Qi Wang, Marco Federici, Herke van Hoof
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes
Zecheng Hao, Jianhao Ding, Tong Bu et al.
Bridging the Gap to Real-World Object-Centric Learning
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk et al.
Broken Neural Scaling Laws
Ethan Caballero, Kshitij Gupta, Irina Rish et al.
BSTT: A Bayesian Spatial-Temporal Transformer for Sleep Staging
Yuchen Liu, Ziyu Jia
Budgeted Training for Vision Transformer
zhuofan xia, Xuran Pan, Xuan Jin et al.
Building a Subspace of Policies for Scalable Continual Learning
Jean-Baptiste Gaya, Thang Doan, Lucas Caccia et al.
Building Normalizing Flows with Stochastic Interpolants
Michael Samuel Albergo, Eric Vanden-Eijnden
Calibrating Sequence likelihood Improves Conditional Language Generation
Yao Zhao, Mikhail Khalman, Rishabh Joshi et al.
Calibrating the Rigged Lottery: Making All Tickets Reliable
Bowen Lei, Ruqi Zhang, Dongkuan Xu et al.
Calibrating Transformers via Sparse Gaussian Processes
Wenlong Chen, Yingzhen Li