Papers
Adapting to Evolving Adversaries with Regularized Continual Robust Training
Sihui Dai, Christian Cianfarani, Vikash Sehwag et al.
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
Wei Dai, Peilin Chen, Malinda Lu et al.
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
Hao Dai, Jagmohan Chauhan
Generalization of noisy SGD in unbounded non-convex settings
Leello Tadesse Dadi, Volkan Cevher
Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning
Mahavir Dabas, Si Chen, Charles Fleming et al.
On Temperature Scaling and Conformal Prediction of Deep Classifiers
Lahav Dabah, Tom Tirer
Causal Abstraction Learning based on the Semantic Embedding Principle
Gabriele D’Acunto, Fabio Massimo Zennaro, Yorgos Felekis et al.
SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders
Bartosz Cywiński, Kamil Deja
Robust Autonomy Emerges from Self-Play
Marco Cusumano-Towner, David Hafner, Alexander Hertzberg et al.
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael Noseworthy et al.
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao et al.
Enhancing Target-unspecific Tasks through a Features Matrix
Fangming Cui, Yonggang Zhang, Xuan Wang et al.
Human Cognition-Inspired Hierarchical Fuzzy Learning Machine
Junbiao Cui, Qin Yue, Jianqing Liang et al.
InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
Tianyu Cui, Song-Jun Xu, Artem Moskalev et al.
An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
Jingyi Cui, Hongwei Wen, Yisen Wang
Calibrating Video Watch-time Predictions with Credible Prototype Alignment
Chao Cui, Shisong Tang, Fan Li et al.
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Wei Peng, Adriel Kuek et al.
OR-Bench: An Over-Refusal Benchmark for Large Language Models
Justin Cui, Wei-Lin Chiang, Ion Stoica et al.
Prediction-Powered E-Values
Daniel Csillag, Claudio Jose Struchiner, Guilherme Tegoni Goedert
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan et al.
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
Corinna Coupette, Jeremy Wayland, Emily Simons et al.
BARNN: A Bayesian Autoregressive and Recurrent Neural Network
Dario Coscia, Max Welling, Nicola Demo et al.
Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors
Matei Gabriel Cosa, Marek Elias
FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered Inference
Stefano Cortinovis, Francois Caron