Spotlight Papers
1,421 papers found • Page 9 of 29
Learnable Sampler Distillation for Discrete Diffusion Models
Feiyang Fu, Tongxian Guo, Zhaoqiang Liu
Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures
Dongzhe Zheng, Wenjie Mei
Learning Interestingness in Automated Mathematical Theory Formation
George Tsoukalas, Rahul Saha, Amitayush Thakur et al.
Learning Parametric Distributions from Samples and Preferences
Marc Jourdan, Gizem Yüce, Nicolas Flammarion
Learning Robust Vision-Language Models from Natural Latent Spaces
Zhangyun Wang, Ni Ding, Aniket Mahanti
Learning Safety Constraints for Large Language Models
Xin Chen, Yarden As, Andreas Krause
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun Jacob et al.
Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models
Chantal Shaib, Vinith Suriyakumar, Byron Wallace et al.
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.
LeMiCa: Lexicographic Minimax Path Caching for Efficient Diffusion-Based Video Generation
Huanlin Gao, Ping Chen, Fuyuan Shi et al.
Less is More: Improving LLM Alignment via Preference Data Selection
Xun Deng, Han Zhong, Rui Ai et al.
Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection
Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.
Light-Weight Diffusion Multiplier and Uncertainty Quantification for Fourier Neural Operators
Albert Matveev, Sanmitra Ghosh, Aamal Hussain et al.
Lightweight Protocols for Distributed Private Quantile Estimation
Anders Aamand, Fabrizio Boninsegna, Abigail Gentle et al.
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
Emilia Magnani, Marvin Pförtner, Tobias Weber et al.
LipsNet++: Unifying Filter and Controller into a Policy Network
Xujie Song, Liangfa Chen, Tong Liu et al.
LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
Qianyue Hao, Yiwen Song, Qingmin Liao et al.
LLM Meeting Decision Trees on Tabular Data
Hangting Ye, Jinmeng Li, He Zhao et al.
Local Identifying Causal Relations in the Presence of Latent Variables
Zheng Li, Zeyu Liu, Feng Xie et al.
Locality in Image Diffusion Models Emerges from Data Statistics
Artem Lukoianov, Chenyang Yuan, Justin Solomon et al.
LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul McVay, Sergio Arnaud, Ada Martin et al.
LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering
Jonas Kulhanek, Marie-Julie Rakotosaona, Fabian Manhardt et al.
LogicTree: Improving Complex Reasoning of LLMs via Instantiated Multi-step Synthetic Logical Data
Zehao Wang, Lin Yang, Jie Wang et al.
Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei et al.
Long-Tailed Recognition via Information-Preservable Two-Stage Learning
Fudong Lin, Xu Yuan
LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers
Yusuf Dalva, Hidir Yesiltepe, Pinar Yanardag
Lost in Transmission: When and Why LLMs Fail to Reason Globally
Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan et al.
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti et al.
Low-degree evidence for computational transition of recovery rate in stochastic block model
Jingqiu Ding, Yiding Hua, Lucas Slot et al.
MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series
Payal Mohapatra, Yueyuan Sui, Akash Pandey et al.
MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
Mahir Labib Dihan, Tanvir Hassan, Md Tanvir Parvez et al.
MARS-VFL: A Unified Benchmark for Vertical Federated Learning with Realistic Evaluation
Wei Shen, Weiqi Liu, Mingde Chen et al.
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
Hao Chen, Yujin Han, Fangyi Chen et al.
Mastering Board Games by External and Internal Planning with Language Models
John Schultz, Jakub Adamek, Matej Jusup et al.
MCU: An Evaluation Framework for Open-Ended Game Agents
Xinyue Zheng, Haowei Lin, Kaichen He et al.
MDReID: Modality-Decoupled Learning for Any-to-Any Multi-Modal Object Re-Identification
Yingying Feng, Jie Li, Jie Hu et al.
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
Emile Anand, Ishani Karmarkar, Guannan Qu
Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks
Ann Huang, Satpreet Harcharan Singh, Flavio Martinelli et al.
Measuring and Guiding Monosemanticity
Ruben Härle, Felix Friedrich, Manuel Brack et al.
Measuring Fingerprints of Web-filtered Text Datasets and Fingerprint Propagation Through Training
Youssef Mansour, Reinhard Heckel
Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
Phillip Guo, Aaquib Syed, Abhay Sheshadri et al.
MedChain: Bridging the Gap Between LLM Agents and Clinical Practice with Interactive Sequence
Jie Liu, Wenxuan Wang, Zizhan Ma et al.
Memory-Enhanced Neural Solvers for Routing Problems
Felix Chalumeau, Refiloe Shabe, Noah De Nicola et al.
Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning
Gunshi Gupta, Karmesh Yadav, Zsolt Kira et al.
MesaTask: Towards Task-Driven Tabletop Scene Generation via 3D Spatial Reasoning
Jinkun Hao, Naifu Liang, Zhen Luo et al.
Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning
Jian Liu, Jing Xu, Song Guo et al.
Meta CLIP 2: A Worldwide Scaling Recipe
Yung-Sung Chuang, Yang Li, Dong Wang et al.
MetaGS: A Meta-Learned Gaussian-Phong Model for Out-of-Distribution 3D Scene Relighting
Yumeng He, Yunbo Wang
MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization
Da Chang, Ganzhao Yuan