Papers
ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
Jianrong Lu, Zhiyu Zhu, Junhui Hou
Second-Order Min-Max Optimization with Lazy Hessians
Lesi Chen, Chengchang Liu, Jingzhao Zhang
Influence Functions for Scalable Data Attribution in Diffusion Models
Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae et al.
Epistemic Monte Carlo Tree Search
Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan et al.
Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
Francisco Eiras, Aleksandar Petrov, Philip Torr et al.
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
Raphael T. Husistein, Markus Reiher, Marco Eckhoff
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski
Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
Jingyuan Zhang, Yiyang Duan, Shuaicheng Niu et al.
Fast Summation of Radial Kernels via QMC Slicing
Johannes Hertrich, Tim Jahn, Michael Quellmalz
CtrLoRA: An Extensible and Efficient Framework for Controllable Image Generation
Yifeng Xu, Zhenliang He, Shiguang Shan et al.
Pyramidal Flow Matching for Efficient Video Generative Modeling
Yang Jin, Zhicheng Sun, Ningyuan Li et al.
Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment
Naoya Hasegawa, Issei Sato
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol et al.
Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling
Guiyu Zhang, Huan-ang Gao, Zijian Jiang et al.
Simulating Human-like Daily Activities with Desire-driven Autonomy
Yiding Wang, Yuxuan Chen, Fangwei Zhong et al.
MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
Sheng Wang, Liheng Chen, Pengan CHEN et al.
Shape as Line Segments: Accurate and Flexible Implicit Surface Representation
Siyu Ren, Junhui Hou
Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings
Hossein Mirzaei, Mackenzie W Mathis
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Xiaoming Shi, Shiyu Wang, Yuqi Nie et al.
Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
Anh Tong, Thanh Nguyen-Tang, Dongeun Lee et al.
HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts
Mengqi Liao, Wei Chen, Junfeng Shen et al.
Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Elliott Ash et al.
Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility
Martin Kuo, Jingyang Zhang, Jianyi Zhang et al.
Rethinking Reward Model Evaluation: Are We Barking up the Wrong Tree?
Xueru Wen, Jie Lou, Yaojie Lu et al.
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Yuze Ge, Rujun Jiang