Papers
A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
Zilin Kang, Chenyuan Hu, Yu Luo et al.
Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
Mingyu Kang, Yong Suk Choi
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin Singh Kang, Landon Butler, Abhineet Agarwal et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
Zhaoxuan Kan, Husheng Han, Shangyi Shi et al.
An analytic theory of creativity in convolutional diffusion models
Mason Kamb, Surya Ganguli
Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp et al.
Towards Better-than-2 Approximation for Constrained Correlation Clustering
Andreas Kalavas, Evangelos Kipouridis, Nithin Varma
UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model
Timo Kaiser, Thomas Norrenbrock, Bodo Rosenhahn
Selective Preference Aggregation
Shreyas Kadekodi, Hayden Mctavish, Berk Ustun
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela Van Der Schaar
Grokking Beyond the Euclidean Norm of Model Parameters
Tikeng Notsawo Pascal Junior, Guillaume Dumas, Guillaume Rabusseau
Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models
Mingi Jung, Saehyung Lee, Eunji Kim et al.
Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
Jaeheun Jung, Jaehyuk Lee, Chang-Hae Jung et al.
Agent-Centric Actor-Critic for Asynchronous Multi-Agent Reinforcement Learning
Whiyoung Jung, Sunghoon Hong, Deunsol Yoon et al.
Preference-CFR: Beyond Nash Equilibrium for Better Game Strategies
Qi Ju, Thomas Tellier, Meng Sun et al.
Watch Out Your Album! On the Inadvertent Privacy Memorization in Multi-Modal Large Language Models
Tianjie Ju, Yi Hua, Hao Fei et al.
Learning Parametric Distributions from Samples and Preferences
Marc Jourdan, Gizem Yüce, Nicolas Flammarion
All-atom Diffusion Transformers: Unified generative modelling of molecules and materials
Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao et al.
Approximate Differential Privacy of the ℓ_2 Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
Taj Jones-Mccormick, Aukosh Jagannath, Subhabrata Sen
Adversaries Can Misuse Combinations of Safe Models
Erik Jones, Anca Dragan, Jacob Steinhardt
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics
Haoming Jing, Yorie Nakahira