Cover Image

Label Attention Network for Temporal Sets Prediction: You Were Looking at a Wrong Self-Attention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kovtun, Elizaveta, Boeva, Galina, Shulga, Andrey, Zaytsev, Alexey
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
by: Kostenok, Elizaveta, et al.
Published: (2023)

PINE: Pipeline for Important Node Exploration in Attributed Networks
by: Kovtun, Elizaveta, et al.
Published: (2025)

Hiding Backdoors within Event Sequence Data via Poisoning Attacks
by: Ermilova, Alina, et al.
Published: (2023)

DeNOTS: Stable Deep Neural ODEs for Time Series
by: Kuleshov, Ilya, et al.
Published: (2024)

Holistic Uncertainty Estimation For Open-Set Recognition
by: Erlygin, Leonid, et al.
Published: (2024)

Language steering in latent space to mitigate unintended code-switching
by: Goncharov, Andrey, et al.
Published: (2025)

Uniting contrastive and generative learning for event sequences models
by: Yugay, Aleksandr, et al.
Published: (2024)

Continuous-time convolutions model of event sequences
by: Zhuzhel, Vladislav, et al.
Published: (2023)

Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
by: Sakhno, Artem, et al.
Published: (2026)

FOCAL-Attention for Heterogeneous Multi-Label Prediction
by: Zhang, Chenghao, et al.
Published: (2026)

Looking around you: external information enhances representations for event sequences
by: Sokerin, Petr, et al.
Published: (2025)

Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
by: Koldasbayeva, Diana, et al.
Published: (2025)

Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize?
by: Kuvshinova, Kseniia, et al.
Published: (2024)

Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
by: Proskura, Polina, et al.
Published: (2024)

Parameter-Efficient Neural CDEs via Implicit Function Jacobians
by: Kuleshov, Ilya, et al.
Published: (2025)

Never Skip a Batch: Continuous Training of Temporal GNNs via Adaptive Pseudo-Supervision
by: Panyshev, Alexander, et al.
Published: (2025)

Spatio-Temporal Attention Network for Epileptic Seizure Prediction
by: Li, Zan, et al.
Published: (2025)

Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction
by: Huang, Zhixin, et al.
Published: (2024)

Kernelized Edge Attention: Addressing Semantic Attention Blurring in Temporal Graph Neural Networks
by: Waghmare, Govind, et al.
Published: (2026)

Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
by: Serov, Egor, et al.
Published: (2026)

U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
by: Kuleshov, Ilya, et al.
Published: (2026)

When an LLM is apprehensive about its answers -- and when its uncertainty is justified
by: Sychev, Petr, et al.
Published: (2025)

Complexity-aware fine-tuning
by: Goncharov, Andrey, et al.
Published: (2025)

Collusion Detection with Graph Neural Networks
by: Gomes, Lucas, et al.
Published: (2024)

Spatio-Temporal Attention Graph Neural Network: Explaining Causalities With Attention
by: Koistinen, Kosti, et al.
Published: (2026)

A theoretical framework for self-supervised contrastive learning for continuous dependent data
by: Marusov, Alexander, et al.
Published: (2025)

Normalizing self-supervised learning for provably reliable Change Point Detection
by: Bazarova, Alexandra, et al.
Published: (2024)

WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection
by: Stepikin, Alexander, et al.
Published: (2025)

Some Attention is All You Need for Retrieval
by: Michalak, Felix, et al.
Published: (2025)

Feature Clock: High-Dimensional Effects in Two-Dimensional Plots
by: Ovcharenko, Olga, et al.
Published: (2024)

You Need Better Attention Priors
by: Litman, Elon, et al.
Published: (2026)

Orthogonal Self-Attention
by: Zhang, Leo, et al.
Published: (2026)

Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
by: Wei, Hui, et al.
Published: (2024)

Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks
by: Park, Eunjeong, et al.
Published: (2026)

Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models
by: Gerber, Isaac
Published: (2025)

Attention Is Not What You Need
by: Chong, Zhang
Published: (2025)

STRIDE: Structure and Embedding Distillation with Attention for Graph Neural Networks
by: Ahluwalia, Anshul, et al.
Published: (2023)

Spatio-Temporal Demand Prediction for Food Delivery Using Attention-Driven Graph Neural Networks
by: Bhat, Rabia Latief, et al.
Published: (2025)

Attention is All You Need Until You Need Retention
by: Yaslioglu, M. Murat
Published: (2025)

Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
by: Yugay, Aleksandr, et al.
Published: (2026)