3/25/2026
JaGuard: Position Error Correction of GNSS Jamming with Deep Temporal Graphs
Deep temporal graph method for correcting GNSS positioning errors from jamming attacks.
3/25/2026
Graph Variate Neural Networks
Graph neural network architecture for modeling spatio-temporal signals with dynamic structure.
3/25/2026
FTTE: Enabling Federated and Resource-Constrained Deep Edge Intelligence
Federated learning framework for training deep models on resource-constrained edge devices.
3/25/2026
Counterfactual Identifiability via Dynamic Optimal Transport
Method for identifying counterfactuals from observational data using optimal transport theory.
3/25/2026
Guided Star-Shaped Masked Diffusion
Novel sampling algorithm for masked diffusion models improving generation quality and efficiency.
3/25/2026
CSI-4CAST: A Hybrid Deep Learning Model for CSI Prediction with Comprehensive Robustness and Generalization Testing
Deep learning model for channel state information prediction in MIMO systems with robustness testing.
3/25/2026
On-device Semantic Selection Made Low Latency and Memory Efficient with Monolithic Forwarding
Optimizes on-device semantic selection with cross-encoder rerankers for retrieval, agent memory, and recommendations via monolithic forwarding.
3/25/2026
GUIrilla: A Scalable Framework for Automated Desktop UI Exploration
Scalable framework for automated desktop UI exploration to generate training data for LLM-based GUI understanding and automation.
3/25/2026
Parameter-Free Clustering via Self-Supervised Consensus Maximization (Extended Version)
Parameter-free clustering framework using self-supervised consensus maximization without requiring hyperparameter tuning.
3/25/2026
Data-Efficient and Robust Trajectory Generation through Pathlet Dictionary Learning
Pathlet dictionary learning approach for robust and interpretable trajectory generation in privacy-preserving urban mobility applications.
3/25/2026
Latent Diffusion Inversion Requires Understanding the Latent Space
Studies model inversion attacks on latent diffusion models, showing non-uniform memorization patterns in latent space.
3/25/2026
Mitigating the Curse of Detail: Scaling Arguments for Feature Learning and Sample Complexity
Theoretical analysis of feature learning mechanisms and implicit bias in deep networks, proposing analytical scaling arguments.
3/25/2026
Arc Gradient Descent: A Geometrically Motivated Gradient Descent-based Optimiser with Phase-Aware, User-Controlled Step Dynamics (proof-of-concept)
Presents Arc Gradient Descent optimizer with phase-aware step dynamics, evaluated on Rosenbrock function and ML datasets.
3/25/2026
DP-FedSOFIM: Differentially Private Federated Stochastic Optimization using Regularized Fisher Information Matrix
Proposes differentially private federated learning optimization using regularized Fisher information matrix for faster convergence under privacy constraints.
3/25/2026
Does Privacy Always Harm Fairness? Data-Dependent Trade-offs via Chernoff Information Neural Estimation
Uses Chernoff information to characterize trade-offs between fairness, privacy, and accuracy in machine learning systems.
3/25/2026
Universal Approximation Theorem for Input-Connected Multilayer Perceptrons
Theoretical analysis of input-connected MLPs with direct connections from input to hidden neurons and universal approximation properties.
3/25/2026
Representational Homomorphism Predicts and Improves Compositional Generalization In Transformer Language Model
Introduces homomorphism error metric to measure representational inconsistencies and predict compositional generalization failures in transformers.
3/25/2026
How Understanding Forecast Uncertainty Resolves the Explainability Problem in Machine Learning Models
Analyzes forecast uncertainty in ML model explainability, arguing uncertainty at decision boundaries explains LIME/SHAP instability.
3/25/2026
FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
Brain-inspired routing method with temporal-ensemble experts for general continual learning from non-stationary data streams.
3/25/2026
T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Proposes one-to-one channel-head binding method for imputing missing values in multivariate time series data.
3/25/2026
When Sensors Fail: Temporal Sequence Models for Robust PPO under Sensor Drift
Studies robustness of PPO reinforcement learning under sensor drift using temporal sequence models to handle partial observability.
3/25/2026
MJ1: Multimodal Judgment via Grounded Verification
arXiv paper MJ1: multimodal judge trained with RL enforcing visual grounding through structured verification chains and counterfactual consistency rewards.
3/25/2026
Multi-Station WiFi CSI Sensing Framework Robust to Station-wise Feature Missingness and Limited Labeled Data
arXiv paper proposing WiFi CSI sensing framework handling station-wise feature missingness and limited labeled data in multi-station deployments.
3/25/2026
A Stability-Aware Frozen Euler Autoencoder for Physics-Informed Tracking in Continuum Mechanics (SAFE-PIT-CM)
arXiv paper SAFE-PIT-CM: autoencoder with frozen Euler solver for recovering material diffusion coefficients from continuum mechanics data.
3/25/2026
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
arXiv paper proposing key deletion approach for machine unlearning designed at model development stage rather than post-hoc, addressing privacy regulations and data errors.
3/25/2026
PRISM: Demystifying Retention and Interaction in Mid-Training
arXiv paper PRISM: empirical study of mid-training design choices across 7 LLM base models showing consistent +15 to +40 point gains from 27B token sequences.
3/25/2026
Elastic Weight Consolidation Done Right for Continual Learning
arXiv paper systematically analyzing Elastic Weight Consolidation for continual learning, revealing suboptimal importance estimation and proposing improvements.
3/25/2026
A Dynamic Bayesian and Machine Learning Framework for Quantitative Evaluation and Prediction of Operator Situation Awareness in Nuclear Power Plants
arXiv paper proposing DBML SA framework using dynamic Bayesian machine learning to evaluate operator situation awareness in nuclear control environments.
3/25/2026
MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels
arXiv paper presenting MemReward, graph-based experience memory framework reducing human labeling needs for LLM reward prediction in RL post-training.
3/25/2026
Global Convergence of Multiplicative Updates for the Matrix Mechanism: A Collaborative Proof with Gemini 3
arXiv paper analyzing fixed-point iterations for nuclear norm optimization in private machine learning, proved with Gemini 3 collaboration.
3/25/2026
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
arXiv paper presenting FIPO reinforcement learning algorithm for improving reasoning in LLMs through fine-grained credit assignment beyond outcome-based rewards.
3/25/2026
MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
arXiv paper proposing Memory-Keyed Attention (MKA) to reduce KV cache memory costs in long-context LLM inference without sacrificing representation quality.
3/25/2026
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
Algorithm for optimal multi-task dataset mixture selection in LLM supervised fine-tuning. Addresses heterogeneous learning dynamics and overfitting.
3/25/2026
Uncertainty Quantification for Distribution-to-Distribution Flow Matching in Scientific Imaging
Uncertainty quantification methods for distribution-to-distribution generative models in scientific imaging. Ensures trustworthy cell and medical image generation.
3/25/2026
CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning
Reinforcement learning post-training for virtual cell models to enforce biological constraints. Improves generative model reliability for drug discovery.
3/25/2026
Inference of Multiscale Gaussian Graphical Model
Gaussian Graphical Models with simultaneous clustering and graph inference for high-dimensional data. Dimensionality reduction approach.
3/25/2026
HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Hyperdimensional binary encoding method for molecular structures in drug discovery. Replaces expensive biophysical calculations.
3/25/2026
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles
Bilevel optimization algorithm using first-order methods for nonconvex-strongly-convex problems. Theoretical optimization analysis.
3/25/2026
All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks
Quantum machine learning circuits using SU(2) equivariance and spin networks. Geometric constraints for variational quantum algorithms.
3/25/2026
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines
Weighted Support Vector Machines for classification and probability estimation. Classic machine learning method with applications.
3/25/2026
Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design
Dynamic scheduling system for efficient large model training across GPU clusters. Addresses training efficiency and resource utilization.
3/25/2026
Smart Bilingual Focused Crawling of Parallel Documents
Web crawling method using neural networks to efficiently find parallel bilingual documents. Targets document discovery for translation.
3/25/2026
SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing
Network packet queuing optimization technique for low-latency applications. Infrastructure networking approach.
3/25/2026
Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning
Self-trained fine-tuning paradigm for LLMs on table understanding tasks like NL-to-Code and data cleaning. Reduces need for expensive human labeling.
3/25/2026
Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
Continual learning technique combining parameter-efficient fine-tuning with vision transformers to prevent catastrophic forgetting. Addresses sequential task adaptation.
3/25/2026
LatentQA: Teaching LLMs to Decode Activations Into Natural Language
Method for training LLMs to explain their own internal activations using natural language probes. Advances LLM interpretability research.
3/25/2026
EmbBERT: Attention Under 2 MB Memory
Transformer attention mechanism compressed to run in under 2MB memory for IoT and wearable devices. Enables NLP deployment on ultra-constrained hardware.
3/25/2026
Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation
Graph filtering method for multimodal recommendation systems without training overhead. Addresses computational efficiency in recommender systems.
3/25/2026
Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions
Study redefining non-IID data heterogeneity in federated learning by migrating from label to embedding-level task-specific distributions.
3/25/2026
Learning dynamically inspired bases for Koopman and transfer operator approximation
Learning dynamically-inspired bases for Koopman and transfer operator approximation in complex nonlinear dynamical systems.