3/25/2026
Can Graph Foundation Models Generalize Over Architecture?
Studies whether graph foundation models can generalize across different GNN architectures and graph characteristics, revealing limitations in current approaches.
3/25/2026
Robustness Quantification and Uncertainty Quantification: Comparing Two Methods for Assessing the Reliability of Classifier Predictions
Compares robustness quantification and uncertainty quantification methods for assessing classifier prediction reliability under distribution shift.
3/25/2026
A Sobering Look at Tabular Data Generation via Probabilistic Circuits
Critical analysis of tabular data generation via probabilistic circuits, questioning progress claims and evaluation protocols in current benchmarks.
3/25/2026
Assessing the Robustness of Climate Foundation Models under No-Analog Distribution Shifts
Evaluates robustness of climate foundation models under out-of-distribution shifts from unprecedented climate states.
3/25/2026
Generalization Bounds for Physics-Informed Neural Networks for the Incompressible Navier-Stokes Equations
Theoretical generalization bounds for physics-informed neural networks solving incompressible Navier-Stokes equations.
3/25/2026
MsFormer: Enabling Robust Predictive Maintenance Services for Industrial Devices
MsFormer transformer-based framework for predictive maintenance in industrial IoT environments with complex sensor data dependencies.
3/25/2026
Policy-based Tuning of Autoregressive Image Models with Instance- and Distribution-Level Rewards
Reinforcement learning approach for training autoregressive image models with policy-based tuning optimizing quality and diversity simultaneously.
3/25/2026
SpecXMaster Technical Report
AI system for automated spectroscopy interpretation in scientific discovery, reducing human bias in spectral analysis.
3/25/2026
Polaris: A G\"odel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair
Polaris framework enabling self-improving agents for small language models through policy repair via experience abstraction and code modifications.
3/25/2026
A Bayesian Learning Approach for Drone Coverage Network: A Case Study on Cardiac Arrest in Scotland
Bayesian learning framework for designing drone-assisted AED delivery networks in emergency medical services.
3/25/2026
DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models
Adaptive prompt routing mechanism for selecting appropriate LLM or generative model based on input prompts, balancing fidelity and diversity.
3/25/2026
A Schr\"odinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
Mathematical framework for solving high-dimensional stochastic optimal control problems with long horizons using Schrödinger eigenfunction methods.
3/25/2026
Sparser, Faster, Lighter Transformer Language Models
Sparse packing format and CUDA kernels leveraging unstructured sparsity in LLM feedforward layers to reduce computational costs and model size.
3/25/2026
A One-Inclusion Graph Approach to Multi-Group Learning
Tight upper bounds on sample complexity for multi-group learning using one-inclusion graph prediction strategy and bipartite matching.
3/25/2026
General Machine Learning: Theory for Learning Under Variable Regimes
Foundational theoretical framework for learning under regime variation where learner, memory state, and evaluation conditions evolve over time.
3/25/2026
GEM: Guided Expectation-Maximization for Behavior-Normalized Candidate Action Selection in Offline RL
Offline reinforcement learning method using guided expectation-maximization for action selection from multimodal action distributions in fixed datasets.
3/25/2026
Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning
Model-based reinforcement learning using neural ODEs and SDEs to capture stochastic dynamics in fully and partially observed environments.
3/25/2026
A Learning Method with Gap-Aware Generation for Heterogeneous DAG Scheduling
End-to-end reinforcement learning framework for heterogeneous DAG scheduling with gap-aware generation enabling rapid schedule adaptation across environments.
3/25/2026
Permutation-Symmetrized Diffusion for Unconditional Molecular Generation
Diffusion model for unconditional molecular generation using permutation symmetry on quotient manifolds to enforce invariance in point-cloud generation.
3/25/2026
SafeSeek: Universal Attribution of Safety Circuits in Language Models
Mechanistic interpretability framework identifying and attributing safety circuits in LLMs responsible for alignment, jailbreak, and backdoor behaviors.
3/25/2026
A Comparative Study of Machine Learning Models for Hourly Forecasting of Air Temperature and Relative Humidity
Comparative study of seven ML models (XGBoost, LSTM, CNN-LSTM, etc.) for hourly air temperature and humidity forecasting in Chongqing.
3/25/2026
Off-Policy Value-Based Reinforcement Learning for Large Language Models
Off-policy value-based reinforcement learning framework for LLMs enabling improved data utilization and sample efficiency for long-horizon tasks.
3/25/2026
Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation
Energy-based model for graph generation using transport-aligned sampling to improve efficiency and quality in discrete domain generation.
3/25/2026
SortedRL: Accelerating RL Training for LLMs through Online Length-Aware Scheduling
Length-aware scheduling method accelerating reinforcement learning training for LLMs by optimizing rollout phase efficiency during chain-of-thought generation.
3/25/2026
Similarity-Aware Mixture-of-Experts for Data-Efficient Continual Learning
Continual learning framework using mixture-of-experts with similarity awareness for data-efficient adaptation to new tasks with limited samples.
3/25/2026
End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions
Computationally efficient reinforcement learning algorithm for linear function approximation in MDPs satisfying linear Bellman completeness.
3/25/2026
Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
Federated learning approach combining differential privacy and Byzantine robustness to protect against both data leakage and adversarial server attacks.
3/25/2026
Estimating Flow Velocity and Vehicle Angle-of-Attack from Non-invasive Piezoelectric Structural Measurements Using Deep Learning
Deep learning method for estimating aerodynamic variables (velocity, angle-of-attack) from piezoelectric sensor measurements on aircraft structures.
3/25/2026
Evaluating Prompting Strategies for Chart Question Answering with Large Language Models
Systematic evaluation of prompting strategies (zero-shot, few-shot, chain-of-thought) for chart question answering across GPT-3.5, GPT-4, and GPT-4o models on ChartQA dataset.
3/25/2026
TIPS: Turn-Level Information-Potential Reward Shaping for Search-Augmented LLMs
TIPS framework improves RL training for search-augmented LLMs via turn-level reward shaping, addressing sparse rewards and credit assignment in reasoning tasks.
3/25/2026
The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis
Multi-agent reinforcement learning agents develop efficient private communication protocol; performance drops with human-comprehensible language enforced.
3/25/2026
Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-structure prediction
CHANRG benchmark reveals limited generalization of RNA secondary-structure prediction models. 170K structured RNA families dataset.
3/25/2026
Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study
Quantitative assessment of reference retrieval errors from 5 LLM platforms on 2,000 medical literature references. Evaluates Grok-2, ChatGPT, Gemini, Perplexity, DeepSeek.
3/25/2026
Intelligence Inertia: Physical Principles and Applications
Theoretical paper on thermodynamic principles and computational costs of maintaining symbolic interpretability in AI systems.
3/25/2026
Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
Theoretical analysis of low-rank knowledge distillation for LLMs with convergence and generalization guarantees. Covers compression techniques for efficient deployment.
3/25/2026
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection
Quantum-enhanced graph neural network for network intrusion detection exploiting relational dependencies in network traffic.
3/25/2026
Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks
Quantum federated autoencoder for anomaly detection in IoT networks using distributed learning without centralizing raw data.
3/25/2026
SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts
Multimodal fusion framework for predicting synthetic lethality in cancer drug development. Domain-specific bioinformatics research.
3/25/2026
Latent Style-based Quantum Wasserstein GAN for Drug Design
Quantum Wasserstein GAN for de novo drug design using generative AI. Focuses on drug discovery rather than ML applications or tools.
3/25/2026
Probabilistic modeling over permutations using quantum computers
Quantum computing approach for probabilistic modeling over permutation-structured data using super-exponential symmetric group Fourier transform speedup.
3/25/2026
Computational Arbitrage in AI Model Markets
Framework for computational arbitrage in AI model markets where arbitrageurs allocate inference budget across competing providers to undercut pricing.
3/25/2026
mmFHE: mmWave Sensing with End-to-End Fully Homomorphic Encryption
First system enabling fully homomorphic encryption for end-to-end mmWave radar sensing with composable FHE kernels for signal processing and ML inference.
3/25/2026
Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
Token-level analysis of distributional shifts during RLVR fine-tuning of LLMs, examining mechanisms underlying reasoning improvements.
3/25/2026
Wake Up to the Past: Using Memory to Model Fluid Wake Effects on Robots
Data-driven approach using memory-augmented neural networks to model fluid wake effects for autonomous aerial and aquatic robots.
3/25/2026
Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architectures
Functional component ablation framework analyzing specialization in hybrid language models combining attention with state space models or linear attention.
3/25/2026
OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection
Verifiable synthetic benchmark for LLM-based insider threat detection using deterministic simulation engine to maintain ground truth and cross-artifact consistency.
3/25/2026
Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling
Differential privacy framework for RLHF fine-tuning that decouples reward learning to preserve user privacy in LLM preference-based training.
3/25/2026
Benchmarking Multi-Agent LLM Architectures for Financial Document Processing: A Comparative Study of Orchestration Patterns, Cost-Accuracy Tradeoffs and Production Scaling Strategies
Systematic benchmark comparing four multi-agent LLM orchestration architectures for financial document processing with cost-accuracy tradeoffs and scaling strategies.
3/25/2026
Improving LLM Predictions via Inter-Layer Structural Encoders
Method leveraging intermediate layer representations in LLMs via Inter-Layer Structural Encoders to improve task-specific predictions beyond final-layer features.
3/25/2026
REALITrees: Rashomon Ensemble Active Learning for Interpretable Trees
Active learning approach using Rashomon ensemble for interpretable decision tree induction with direct hypothesis space characterization.