Papers
11,015 papers found
Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker et al.
Learning to Steer Markovian Agents under Model Uncertainty
Jiawei Huang, Vinzenz Thoma, Zebang Shen et al.
Learning Transformer-based World Models with Contrastive Predictive Coding
Maxime Burchi, Radu Timofte
Learning under Temporal Label Noise
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni et al.
Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels
Daning Huang, Hanyang He, John Harlim et al.
Learning View-invariant World Models for Visual Robotic Manipulation
Jing-Cheng Pang, Nan Tang, Kaiyuan Li et al.
Learn Your Reference Model for Real Good Alignment
Alexey Gorbatovski, Boris Shaposhnikov, Alexey Malakhov et al.
Leave-One-Out Stable Conformal Prediction
Kiljae Lee, Yuan Zhang
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
Hantao Zhang, Yuhe Liu, Jiancheng Yang et al.
Less is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models
Lin Zhu, Xinbing Wang, Chenghu Zhou et al.
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
Zhiwei Xu, Zhiyu Ni, Yixin Wang et al.
Let the Code LLM Edit Itself When You Edit the Code
Zhenyu He, Jun Zhang, Shengjie Luo et al.
Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
Yilun Zheng, Xiang Li, Sitao Luan et al.
LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions
Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham et al.
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel et al.
Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD
Ze Peng, Jian Zhang, Yisen Wang et al.
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
Rui Dai, Sile Hu, Xu Shen et al.
Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning
Calarina Muslimani, Matthew E. Taylor
LICO: Large Language Models for In-Context Molecular Optimization
Tung Nguyen, Aditya Grover
LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon et al.
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
Zakhar Shumaylov, Peter Zaika, James Rowbottom et al.
LIFe-GoM: Generalizable Human Rendering with Learned Iterative Feedback Over Multi-Resolution Gaussians-on-Mesh
Jing Wen, Alex Schwing, Shenlong Wang