Saved in:
| Main Authors: | Xu, Yangshuang, Dai, Yuyang, Chang, Liling, Wang, Qi, Dong, Yushun |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.18911 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?
by: Zhao, Kaixiang, et al.
Published: (2026)
by: Zhao, Kaixiang, et al.
Published: (2026)
From Rubrics to Reliable Scores: Evidence-Grounded Text Evaluation with LLM Judges
by: Hong, Yihan, et al.
Published: (2026)
by: Hong, Yihan, et al.
Published: (2026)
Muon is Not That Special: Random or Inverted Spectra Work Just as Well
by: Shumaylov, Zakhar, et al.
Published: (2026)
by: Shumaylov, Zakhar, et al.
Published: (2026)
What Do Latent Action Models Actually Learn?
by: Zhang, Chuheng, et al.
Published: (2025)
by: Zhang, Chuheng, et al.
Published: (2025)
Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion?
by: Sakai, Yusuke, et al.
Published: (2023)
by: Sakai, Yusuke, et al.
Published: (2023)
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
by: Lin, Jinxu, et al.
Published: (2024)
by: Lin, Jinxu, et al.
Published: (2024)
Are Language Models Actually Useful for Time Series Forecasting?
by: Tan, Mingtian, et al.
Published: (2024)
by: Tan, Mingtian, et al.
Published: (2024)
When Does Persona Prompting Actually Help? A Retrieval and Metric Analysis of Expert Role Injection in LLMs
by: Xiao, Shuai, et al.
Published: (2026)
by: Xiao, Shuai, et al.
Published: (2026)
Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)
by: Lade, Ankit Hemant, et al.
Published: (2026)
by: Lade, Ankit Hemant, et al.
Published: (2026)
Explainable Global Wildfire Prediction Models using Graph Neural Networks
by: Chen, Dayou, et al.
Published: (2024)
by: Chen, Dayou, et al.
Published: (2024)
Causal Graph Neural Networks for Wildfire Danger Prediction
by: Zhao, Shan, et al.
Published: (2024)
by: Zhao, Shan, et al.
Published: (2024)
Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
by: Üstek, İrem, et al.
Published: (2024)
by: Üstek, İrem, et al.
Published: (2024)
ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data
by: Lei, Zhenyu, et al.
Published: (2024)
by: Lei, Zhenyu, et al.
Published: (2024)
Proof of Concept: Multi-Target Wildfire Risk Prediction and Large Language Model Synthesis
by: Caron, Nicolas, et al.
Published: (2026)
by: Caron, Nicolas, et al.
Published: (2026)
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
JaxWildfire: A GPU-Accelerated Wildfire Simulator for Reinforcement Learning
by: Çakır, Ufuk, et al.
Published: (2025)
by: Çakır, Ufuk, et al.
Published: (2025)
Rethinking Fair Graph Neural Networks from Re-balancing
by: Li, Zhixun, et al.
Published: (2024)
by: Li, Zhixun, et al.
Published: (2024)
What do Geometric Hallucination Detection Metrics Actually Measure?
by: Yeats, Eric, et al.
Published: (2026)
by: Yeats, Eric, et al.
Published: (2026)
Why Does RLAIF Work At All?
by: Young, Robin
Published: (2026)
by: Young, Robin
Published: (2026)
Characterizing and Predicting Wildfire Evacuation Behavior: A Dual-Stage ML Approach
by: Polock, Sazzad Bin Bashar, et al.
Published: (2026)
by: Polock, Sazzad Bin Bashar, et al.
Published: (2026)
Advancing Wildfire Risk Prediction via Morphology-Aware Curriculum Contrastive Learning
by: Scudo, Fabrizio Lo, et al.
Published: (2025)
by: Scudo, Fabrizio Lo, et al.
Published: (2025)
Predictive and Prescriptive AI toward Optimizing Wildfire Suppression
by: Boussioux, Leonard, et al.
Published: (2026)
by: Boussioux, Leonard, et al.
Published: (2026)
From Projection to Prediction: Beyond Logits for Scalable Language Models
by: Dong, Jianbing, et al.
Published: (2025)
by: Dong, Jianbing, et al.
Published: (2025)
COMPOL: A Unified Neural Operator Framework for Scalable Multi-Physics Simulations
by: Sun, Yifei, et al.
Published: (2025)
by: Sun, Yifei, et al.
Published: (2025)
Forget the Data and Fine-Tuning! Just Fold the Network to Compress
by: Wang, Dong, et al.
Published: (2025)
by: Wang, Dong, et al.
Published: (2025)
WLFM: A Well-Logs Foundation Model for Multi-Task and Cross-Well Geological Interpretation
by: Qi, Zhenyu, et al.
Published: (2025)
by: Qi, Zhenyu, et al.
Published: (2025)
Does Deep Active Learning Work in the Wild?
by: Ren, Simiao, et al.
Published: (2023)
by: Ren, Simiao, et al.
Published: (2023)
Understanding and Guiding Layer Placement in Parameter-Efficient Fine-Tuning of Large Language Models
by: Xu, Yichen, et al.
Published: (2026)
by: Xu, Yichen, et al.
Published: (2026)
From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs
by: Chen, Ruxiao, et al.
Published: (2025)
by: Chen, Ruxiao, et al.
Published: (2025)
A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series
by: Piao, Xihao, et al.
Published: (2026)
by: Piao, Xihao, et al.
Published: (2026)
DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
To Trust Or Not To Trust Your Vision-Language Model's Prediction
by: Dong, Hao, et al.
Published: (2025)
by: Dong, Hao, et al.
Published: (2025)
FlashSVD v1.5: Making Low-Rank Transformers Inference Actually Fast
by: Wu, Wenhao, et al.
Published: (2026)
by: Wu, Wenhao, et al.
Published: (2026)
Can We Predict Your Next Move Without Breaking Your Privacy?
by: Soni, Arpita, et al.
Published: (2025)
by: Soni, Arpita, et al.
Published: (2025)
Long-Term Outlier Prediction Through Outlier Score Modeling
by: Aoki, Yuma, et al.
Published: (2026)
by: Aoki, Yuma, et al.
Published: (2026)
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
Deep Learning with Pretrained 'Internal World' Layers: A Gemma 3-Based Modular Architecture for Wildfire Prediction
by: Jadouli, Ayoub, et al.
Published: (2025)
by: Jadouli, Ayoub, et al.
Published: (2025)
A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
Does Your Neural Network Extrapolate? Feature Engineering as Identifiability Bias for OOD Generalization
by: Aguilar, Leonel, et al.
Published: (2026)
by: Aguilar, Leonel, et al.
Published: (2026)
Similar Items
-
GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?
by: Zhao, Kaixiang, et al.
Published: (2026) -
From Rubrics to Reliable Scores: Evidence-Grounded Text Evaluation with LLM Judges
by: Hong, Yihan, et al.
Published: (2026) -
Muon is Not That Special: Random or Inverted Spectra Work Just as Well
by: Shumaylov, Zakhar, et al.
Published: (2026) -
What Do Latent Action Models Actually Learn?
by: Zhang, Chuheng, et al.
Published: (2025) -
Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion?
by: Sakai, Yusuke, et al.
Published: (2023)