Papers
Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning
Zebang Cheng, Zhi-Qi Cheng, Jun-Yan He et al.
Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism
Ronast Subedi, Lu Wei, Wenhan Gao et al.
Empowering and Assessing the Utility of Large Language Models in Crop Science
Hang Zhang, Jiawei Sun, Renqi Chen et al.
Empowering Visible-Infrared Person Re-Identification with Large Foundation Models
Zhangyi Hu, Bin Yang, Mang Ye
EMR-Merging: Tuning-Free High-Performance Model Merging
Chenyu Huang, Peng Ye, Tao Chen et al.
EMVP: Embracing Visual Foundation Model for Visual Place Recognition with Centroid-Free Probing
Qibo Qiu, Shun Zhang, Haiming Gao et al.
Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting Diversity
Robby Costales, Stefanos Nikolaidis
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis
Zanlin Ni, Yulin Wang, Renping Zhou et al.
End-To-End Causal Effect Estimation from Unstructured Natural Language Data
Nikita Dhawan, Leonardo Cotta, Karen Ullrich et al.
End-to-end Learnable Clustering for Intent Learning in Recommendation
Yue Liu, Shihao Zhu, Jun Xia et al.
End-to-End Ontology Learning with Large Language Models
Andy Lo, Albert Q. Jiang, Wenda Li et al.
End-to-End Video Semantic Segmentation in Adverse Weather using Fusion Blocks and Temporal-Spatial Teacher-Student Learning
Xin Yang, Yan Wending, Michael Bi Mi et al.
Energy-based Epistemic Uncertainty for Graph Neural Networks
Dominik Fuchsgruber, Tom Wollschläger, Stephan Günnemann
Energy-based Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann, Simon Schmid, Bernhard Lehner et al.
Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces
Tobias Schröder, Zijing Ou, Yingzhen Li et al.
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Alexander Kolesov, Petr Mokrov, Igor Udovichenko et al.
Enhancing Chess Reinforcement Learning with Graph Representation
Tomas Rigaux, Hisashi Kashima
Enhancing Consistency-Based Image Generation via Adversarialy-Trained Classification and Energy-Based Discrimination
Shelly Golan, Roy Ganz, Michael Elad
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA
David Smerkous, Qinxun Bai, Li Fuxin
Enhancing Domain Adaptation through Prompt Gradient Alignment
Hoang Phan, Lam Tran, Quyen Tran et al.
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation
Shangding Gu, Laixi Shi, Yuhao Ding et al.
Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers
Chau Pham, Bryan A. Plummer
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
Yuankai Luo, Hongkang Li, Lei Shi et al.
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
Xinhao Yao, Xiaolin Hu, Shenzhi Yang et al.
Enhancing Large Language Models through Adaptive Tokenizers
Mengyu Zheng, Hanting Chen, Tianyu Guo et al.