Papers
11,955 papers found
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
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems
Yewen Fan, Nian Si, Kun Zhang
CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
Xiaohan Wang, Yuehu Liu, Xinhang Song et al.
Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
Yuxin Wen, Arpit Bansal, Hamid Kazemi et al.
Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study
Mingxu Tao, Yansong Feng, Dongyan Zhao
Can CNNs Be More Robust Than Transformers?
Zeyu Wang, Yutong Bai, Yuyin Zhou et al.
Can discrete information extraction prompts generalize across language models?
Nathanaël Carraz Rakotonirina, Roberto Dessi, Fabio Petroni et al.
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
Samuel Maddock, Alexandre Sablayrolles, Pierre Stock
Can Neural Networks Learn Implicit Logic from Physical Reasoning?
Aaron Traylor, Roman Feiman, Ellie Pavlick
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?
Han Zhong, Zhuoran Yang, Zhaoran Wang et al.
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN?
Jie Ren, Zhanpeng Zhou, Qirui Chen et al.
Can We Find Nash Equilibria at a Linear Rate in Markov Games?
Zhuoqing Song, Jason D. Lee, Zhuoran Yang
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models
Denis Kuznedelev, Eldar Kurtić, Elias Frantar et al.
Capturing the Motion of Every Joint: 3D Human Pose and Shape Estimation with Independent Tokens
Sen Yang, Wen Heng, Gang Liu et al.
CASR: Generating Complex Sequences with Autoregressive Self-Boost Refinement
Hongwei Han, Mengyu Zhou, Shi Han et al.