Papers
11,015 papers found
Bandits with Replenishable Knapsacks: the Best of both Worlds
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Jin Li, XIAOPENG ZHANG et al.
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Han Zhou, Xingchen Wan, Lev Proleev et al.
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du et al.
BatteryML: An Open-source Platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng et al.
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan et al.
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
Siqi Kou, Lei Gan, Dequan Wang et al.
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
Bayesian Low-rank Adaptation for Large Language Models
Adam X. Yang, Maxime Robeyns, Xi Wang et al.
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
Konstantin Hess, Valentyn Melnychuk, Dennis Frauen et al.
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
Yongsheng Mei, Mahdi Imani, Tian Lan
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin et al.
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
Jeff Guo, Philippe Schwaller
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Andrew Stavroulakis et al.
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
Haoxuan Li, Chunyuan Zheng, Sihao Ding et al.
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Kristian Kersting
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
Behaviour Distillation
Andrei Lupu, Chris Lu, Jarek Luca Liesen et al.
Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
Xiaolin Sun, Zizhan Zheng
Bellman Optimal Stepsize Straightening of Flow-Matching Models
Bao Nguyen, Binh Nguyen, Viet Anh Nguyen
Benchmarking Algorithms for Federated Domain Generalization
Ruqi Bai, Saurabh Bagchi, David I. Inouye
Benchmarking and Improving Generator-Validator Consistency of Language Models
Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li et al.