Papers
Model Risk-sensitive Offline Reinforcement Learning
Gwangpyo Yoo, Honguk Woo
OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation
Kepan Nan, Rui Xie, Penghao Zhou et al.
Standardizing Structural Causal Models
Weronika Ormaniec, Scott Sussex, Lars Lorch et al.
Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model
Yaxuan Huang, Xili Dai, Jianan Wang et al.
Learning Hierarchical Polynomials of Multiple Nonlinear Features
Hengyu Fu, Zihao Wang, Eshaan Nichani et al.
ELBOing Stein: Variational Bayes with Stein Mixture Inference
Ola Rønning, Eric Nalisnick, Christophe Ley et al.
Training-free LLM-generated Text Detection by Mining Token Probability Sequences
Yihuai Xu, Yongwei Wang, Yifei Bi et al.
Fast training and sampling of Restricted Boltzmann Machines
Nicolas BEREUX, Aurélien Decelle, Cyril Furtlehner et al.
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo et al.
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
AI Sandbagging: Language Models can Strategically Underperform on Evaluations
Teun van der Weij, Felix Hofstätter, Oliver Jaffe et al.
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
Yan Scholten, Stephan Günnemann, Leo Schwinn
Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
Justin Deschenaux, Caglar Gulcehre
DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning
Chao Li, Ziwei Deng, Chenxing Lin et al.
Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh et al.
MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
Xuannan Liu, Zekun Li, Pei Pei Li et al.
COPER: Correlation-based Permutations for Multi-View Clustering
Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang et al.
Regularizing Energy among Training Samples for Out-of-Distribution Generalization
Yiting Chen, Qitian Wu, Junchi Yan
On the Relation between Trainability and Dequantization of Variational Quantum Learning Models
Elies Gil-Fuster, Casper Gyurik, Adrian Perez-Salinas et al.
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector
Jinghan Li, Yuan Gao, Jinda Lu et al.
MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
Masakazu Yoshimura, Teruaki Hayashi, Yota Maeda
SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob et al.