Papers
Knowledge Distillation in Federated Learning: A Practical Guide
Alessio Mora, Irene Tenison, Paolo Bellavista et al.
KnowledgeHub: An End-to-End Tool for Assisted Scientific Discovery
Shinnosuke Tanaka, James Barry, Vishnudev Kuruvanthodi et al.
KTCN: Enhancing Open-World Object Detection with Knowledge Transfer and Class-Awareness Neutralization
Xing Xi, Yangyang Huang, Jinhao Lin et al.
Label Distribution Learning from Logical Label
Yuheng Jia, Jiawei Tang, Jiahao Jiang
Label-efficient Semantic Scene Completion with Scribble Annotations
Song Wang, Jiawei Yu, Wentong Li et al.
Label Leakage in Vertical Federated Learning: A Survey
Yige Liu, Yiwei Lou, Yang Liu et al.
Langshaw: Declarative Interaction Protocols Based on Sayso and Conflict
Munindar P. Singh, Samuel H. Christie V., Amit K. Chopra
LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks
Hung Nguyen, Tobias Clement, Loc Nguyen et al.
Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents
Zihao Zhou, Bin Hu, Chenyang Zhao et al.
Large Language Model Based Multi-agents: A Survey of Progress and Challenges
Taicheng Guo, Xiuying Chen, Yaqi Wang et al.
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
Xingyu Wu, Yan Zhong, Jibin Wu et al.
Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection
Chen Liu, Shibo He, Qihang Zhou et al.
Large Language Models Are Not Strong Abstract Reasoners
Gaël Gendron, Qiming Bao, Michael Witbrock et al.
Large Language Models for Human-AI Co-Creation of Robotic Dance Performances
Allegra De Filippo, Michela Milano
Large Language Models for Time Series: A Survey
Xiyuan Zhang, Ranak Roy Chowdhury, Rajesh K. Gupta et al.
Layered and Staged Monte Carlo Tree Search for SMT Strategy Synthesis
Zhengyang Lu, Stefan Siemer, Piyush Jha et al.
Layered Graph Security Games
Jakub Cerny, Chun Kai Ling, Christian Kroer et al.
Laying the Foundations for Solving FOND HTN Problems: Grounding, Search, Heuristics (and Benchmark Problems)
Mohammad Yousefi, Pascal Bercher
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game
Jianfeng Lu, Yue Chen, Shuqin Cao et al.
Learning a Spiking Neural Network for Efficient Image Deraining
Tianyu Song, Guiyue Jin, Pengpeng Li et al.
Learning-Based Tracking-before-Detect for RF-Based Unconstrained Indoor Human Tracking
Zhi Wu, Dongheng Zhang, Zixin Shang et al.
Learning Big Logical Rules by Joining Small Rules
Céline Hocquette, Andreas Niskanen, Rolf Morel et al.
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
Aneesh Komanduri, Yongkai Wu, Feng Chen et al.
Learning Conditional Preference Networks: An Approach Based on the Minimum Description Length Principle
Pierre-François Gimenez, Jérôme Mengin
Learning Embeddings for Sequential Tasks Using Population of Agents
Mridul Mahajan, Georgios Tzannetos, Goran Radanovic et al.