Papers
Learning Universal Adversarial Perturbation by Adversarial Example
Maosen Li, Yanhua Yang, Kun Wei et al.
Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders
Abhishek Banerjee, Uttaran Bhattacharya, Aniket Bera
Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion
Ruiqi Gao, Jianwen Xie, Siyuan Huang et al.
Leashing the Inner Demons: Self-Detoxification for Language Models
Canwen Xu, Zexue He, Zhankui He et al.
LeSICiN: A Heterogeneous Graph-Based Approach for Automatic Legal Statute Identification from Indian Legal Documents
Shounak Paul, Pawan Goyal, Saptarshi Ghosh
Less Is More: Pay Less Attention in Vision Transformers
Zizheng Pan, Bohan Zhuang, Haoyu He et al.
LGD: Label-Guided Self-Distillation for Object Detection
Peizhen Zhang, Zijian Kang, Tong Yang et al.
Lifelong Generative Modelling Using Dynamic Expansion Graph Model
Fei Ye, Adrian G. Bors
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization
Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli et al.
Lifelong Person Re-identification by Pseudo Task Knowledge Preservation
Wenhang Ge, Junlong Du, Ancong Wu et al.
LIMREF: Local Interpretable Model Agnostic Rule-Based Explanations for Forecasting, with an Application to Electricity Smart Meter Data
Dilini Rajapaksha, Christoph Bergmeir
Linearity-Aware Subspace Clustering
Yesong Xu, Shuo Chen, Jun Li et al.
Linear-Time Verification of Data-Aware Dynamic Systems with Arithmetic
Paolo Felli, Marco Montali, Sarah Winkler
Linking Transformer to Hawkes Process for Information Cascade Prediction (Student Abstract)
Liu Yu, Xovee Xu, Ting Zhong et al.
Liquid Democracy with Ranked Delegations
Markus Brill, Théo Delemazure, Anne-Marie George et al.
Listwise Learning to Rank Based on Approximate Rank Indicators
Thibaut Thonet, Yagmur Gizem Cinar, Eric Gaussier et al.
LITMUS Predictor: An AI Assistant for Building Reliable, High-Performing and Fair Multilingual NLP Systems
Anirudh Srinivasan, Gauri Kholkar, Rahul Kejriwal et al.
Local and Global Convergence of General Burer-Monteiro Tensor Optimizations
Shuang Li, Qiuwei Li
Local and Global Linear Convergence of General Low-Rank Matrix Recovery Problems
Yingjie Bi, Haixiang Zhang, Javad Lavaei
Local Differential Privacy for Belief Functions
Qiyu Li, Chunlai Zhou, Biao Qin et al.
Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning
Roy Zohar, Shie Mannor, Guy Tennenholtz
Locally Fair Partitioning
Pankaj K. Agarwal, Shao-Heng Ko, Kamesh Munagala et al.
Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error
Anamay Chaturvedi, Matthew Jones, Huy Lê Nguyễn
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Biyang Liu, Huimin Yu, Yangqi Long