Cover Image

FoGE: Fock Space inspired encoding for graph prompting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chytas, Sotirios Panagiotis, Chakraborty, Rudrasis, Singh, Vikas
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Concept Attractors in LLMs and their Applications
by: Chytas, Sotirios Panagiotis, et al.
Published: (2025)

Variational Sampling of Temporal Trajectories
by: Nazarovs, Jurijs, et al.
Published: (2024)

Beyond Pooling: Matching for Robust Generalization under Data Heterogeneity
by: Roy, Ayush, et al.
Published: (2026)

Pooling Image Datasets With Multiple Covariate Shift and Imbalance
by: Chytas, Sotirios Panagiotis, et al.
Published: (2024)

Enhancing Machine Learning for Imbalanced Medical Data: A Quantum-Inspired Approach to Synthetic Oversampling (QI-SMOTE)
by: Kashtriya, Vikas, et al.
Published: (2025)

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization
by: Yao, Yiming, et al.
Published: (2025)

FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models
by: Klüttermann, Simon, et al.
Published: (2026)

\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition
by: Lu, Yao, et al.
Published: (2025)

FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection
by: Shen, Yuchen, et al.
Published: (2024)

Causal prompting model-based offline reinforcement learning
by: Yu, Xuehui, et al.
Published: (2024)

Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworks
by: Christophides, Theodoros, et al.
Published: (2024)

Right Time to Learn:Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation
by: Sun, Guanglong, et al.
Published: (2025)

FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records
by: Pang, Chao, et al.
Published: (2025)

DoGE: Domain Reweighting with Generalization Estimation
by: Fan, Simin, et al.
Published: (2023)

The role of positional encodings in the ARC benchmark
by: Costa, Guilherme H. Bandeira, et al.
Published: (2025)

Error Taxonomy-Guided Prompt Optimization
by: Singh, Mayank, et al.
Published: (2026)

Efficient multi-prompt evaluation of LLMs
by: Polo, Felipe Maia, et al.
Published: (2024)

Explanations that reveal all through the definition of encoding
by: Puli, Aahlad, et al.
Published: (2024)

Prompt replay: speeding up grpo with on-policy reuse of high-signal prompts
by: Baroian, Andrei, et al.
Published: (2026)

PQS (Prune, Quantize, and Sort): Low-Bitwidth Accumulation of Dot Products in Neural Network Computations
by: Natesh, Vikas, et al.
Published: (2025)

Margin-calibrated Classifier Guidance for Property-driven Synthesis Planning
by: Laabid, Najwa, et al.
Published: (2026)

It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt
by: Bladon, Stuart, et al.
Published: (2026)

An Explainable Gaussian Process Auto-encoder for Tabular Data
by: Zhang, Wei, et al.
Published: (2025)

Auto-encoding Molecules: Graph-Matching Capabilities Matter
by: Cunow, Magnus, et al.
Published: (2025)

Do traveling waves make good positional encodings?
by: van de Geijn, Chase, et al.
Published: (2025)

P2DT: Mitigating Forgetting in task-incremental Learning with progressive prompt Decision Transformer
by: Wang, Zhiyuan, et al.
Published: (2024)

Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
by: Tao, Qinghua, et al.
Published: (2024)

CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
by: Park, Jongwon, et al.
Published: (2025)

Nonlocal operator learning for fMRI encoding and decoding tasks
by: Kramer, Andreas, et al.
Published: (2026)

Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces
by: Kar, Avik, et al.
Published: (2024)

FoME: A Foundation Model for EEG using Adaptive Temporal-Lateral Attention Scaling
by: Shi, Enze, et al.
Published: (2024)

Brittlebench: Quantifying LLM robustness via prompt sensitivity
by: Romanou, Angelika, et al.
Published: (2026)

Why Pass@k Optimization Can Degrade Pass@1: Prompt Interference in LLM Post-training
by: Barakat, Anas, et al.
Published: (2026)

BaB-prob: Branch and Bound with Preactivation Splitting for Probabilistic Verification of Neural Networks
by: Wang, Fangji, et al.
Published: (2025)

EEG-MFTNet: An Enhanced EEGNet Architecture with Multi-Scale Temporal Convolutions and Transformer Fusion for Cross-Session Motor Imagery Decoding
by: Andrikopoulos, Panagiotis, et al.
Published: (2026)

Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets
by: Lymperopoulos, Panagiotis, et al.
Published: (2024)

Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings
by: Tsoumplekas, Georgios, et al.
Published: (2024)

Humanoid-inspired Causal Representation Learning for Domain Generalization
by: Tao, Ze, et al.
Published: (2025)

Quantum feature encoding optimization
by: Fioravanti, Tommaso, et al.
Published: (2025)

Let Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation
by: Verma, Yogesh, et al.
Published: (2025)