3/3/2026
Vectorized Adaptive Histograms for Sparse Oblique Forests
Vectorized Adaptive Histograms for Sparse Oblique Forests: Method to optimize histogram and sorting tradeoffs in random forest training.
3/3/2026
Detecting Transportation Mode Using Dense Smartphone GPS Trajectories and Transformer Models
SpeedTransformer: Transformer-based model using smartphone GPS data to detect transportation modes, outperforming LSTM baselines.
3/3/2026
Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
Studies catastrophic forgetting in IoT intrusion detection systems under distribution shifts from evolving attack patterns.
3/3/2026
Hereditary Geometric Meta-RL: Nonlocal Generalization via Task Symmetries
Geometric meta-RL approach leveraging task space symmetries for improved generalization in reinforcement learning.
3/3/2026
USE: Uncertainty Structure Estimation for Robust Semi-Supervised Learning
USE introduces lightweight procedure for semi-supervised learning that estimates uncertainty structure to handle out-of-distribution unlabeled data.
3/3/2026
Exact and Asymptotically Complete Robust Verifications of Neural Networks via Quantum Optimization
Quantum optimization approach for exact robust verification of neural networks against adversarial perturbations.
3/3/2026
Weight Updates as Activation Shifts: A Principled Framework for Steering
Establishes equivalence between activation steering and weight-space updates, providing principled foundation for parameter-efficient LLM adaptation.
3/3/2026
Efficient Decoder Scaling Strategy for Neural Routing Solvers
Studies decoder scaling strategies in construction-based neural routing solvers for vehicle routing optimization problems.
3/3/2026
ROKA: Robust Knowledge Unlearning against Adversaries
ROKA addresses machine unlearning robustness against adversarial attacks that exploit knowledge contamination in unlearned models.
3/3/2026
Rooted Absorbed Prefix Trajectory Balance with Submodular Replay for GFlowNet Training
RapTB improves GFlowNet training for fine-tuning LLMs by addressing prefix collapse through trajectory balancing and submodular replay.
3/3/2026
Benchmarking Few-shot Transferability of Pre-trained Models with Improved Evaluation Protocols
FEWTRANS benchmark evaluates few-shot transfer learning of pre-trained models with improved evaluation protocols across 10 datasets.
3/3/2026
Heaviside Low-Rank Support Matrix Machine
HL-SMM introduces Heaviside loss-based support matrix machine for classification of matrix-structured data with noise robustness.
3/3/2026
A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
ESENSC_rev2 proposes polynomial-time feature attribution algorithm as computationally efficient alternative to SHAP using game theory.
3/3/2026
Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence
Antibody introduces defense mechanism against harmful fine-tuning attacks on LLMs by regularizing gradient contributions of poisoned samples.
3/3/2026
FastBUS: A Fast Bayesian Framework for Unified Weakly-Supervised Learning
FastBUS proposes a Bayesian framework for weakly-supervised learning that handles multiple label types efficiently with batch processing.
3/3/2026
Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching
Bridge Matching Sampler for scalable sampling from unnormalized densities using generalized fixed-point diffusion matching.
3/3/2026
Spectral Condition for $\mu$P under Width-Depth Scaling
Spectral condition analysis for maximal update parameterization under joint width-depth scaling in foundation models.
3/3/2026
Learning to Attack: A Bandit Approach to Adversarial Context Poisoning
AdvBandit black-box adaptive attack on neural contextual bandits formulating context poisoning as continuous-armed bandit problem.
3/3/2026
DeepAFL: Deep Analytic Federated Learning
Analytic federated learning approach replacing gradient-based updates with closed-form solutions for improved convergence and scalability.
3/3/2026
Unlearning Evaluation through Subset Statistical Independence
Subset-level evaluation framework for machine unlearning using statistical independence without retraining or membership inference.
3/3/2026
Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
Policy-guided outlier synthesis approach for unsupervised out-of-distribution detection in graph neural networks.
3/3/2026
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
Multi-domain graph pre-training framework for building graph foundation models with theoretical analysis of knowledge transfer.
3/3/2026
IDER: IDempotent Experience Replay for Reliable Continual Learning
IDER method addressing catastrophic forgetting in continual learning with uncertainty calibration for mission-critical deployment.
3/3/2026
Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models
Data-centric framework for adapting diverse time series to large time series models without retraining.
3/3/2026
Frozen Policy Iteration: Computationally Efficient RL under Linear $Q^{\pi}$ Realizability for Deterministic Dynamics
Frozen Policy Iteration algorithm for computationally efficient reinforcement learning under linear Q-function realizability.
3/3/2026
MARS: Harmonizing Multimodal Convergence via Adaptive Rank Search
MARS framework for efficient fine-tuning of multimodal LLMs using adaptive rank search to handle training imbalance across modalities.
3/3/2026
To Use or not to Use Muon: How Simplicity Bias in Optimizers Matters
Analysis of Muon optimizer's simplicity bias and potential downsides compared to Adam for neural network training.
3/3/2026
General Proximal Flow Networks
Generalizes Bayesian Flow Networks with arbitrary divergence/distance functions replacing fixed KL divergence, enabling broader belief-update operators.
3/3/2026
Identifying and Characterising Response in Clinical Trials: Development and Validation of a Machine Learning Approach in Colorectal Cancer
Combines partly conditional modeling with machine learning to identify patient response subgroups in colorectal cancer clinical trials using repeated measures.
3/3/2026
Interpretable Cross-Network Attention for Resting-State fMRI Representation Learning
Self-supervised learning framework for resting-state fMRI using masked reconstruction with cross-attention for interpretable brain network representation learning.
3/3/2026
Identifying the Geographic Foci of US Local News
Proposes geo-foci model for identifying salient geographical locations in US local news coverage to address economic pressures on local journalism.
3/3/2026
Neural Latent Arbitrary Lagrangian-Eulerian Grids for Fluid-Solid Interaction
Neural approach to fluid-solid interaction using latent arbitrary Lagrangian-Eulerian grids for capturing two-way nonlinear interactions in FSI problems.
3/3/2026
Lookahead identification in adversarial bandits: accuracy and memory bounds
Studies identification problem in adversarial multi-armed bandits for selecting arms performing best at future time with accuracy and memory bounds.
3/3/2026
Curation Leaks: Membership Inference Attacks against Data Curation for Machine Learning
Demonstrates membership inference attacks against data curation methods used for private ML, showing curation-based privacy solutions leak training data membership.
3/3/2026
A Gauge Theory of Superposition: Toward a Sheaf-Theoretic Atlas of Neural Representations
Develops gauge-theoretic framework for superposition in LLMs using sheaf-theoretic atlas replacing single-global-dictionary with local semantic charts and Fisher metrics.
3/3/2026
GeMi: A Graph-based, Multimodal Recommendation System for Narrative Scroll Paintings
Graph Neural Network-based recommendation system for multimodal data handling content-based recommendations with user preference incorporation.
3/3/2026
Navigating Time's Possibilities: Plausible Counterfactual Explanations for Multivariate Time-Series Forecast through Genetic Algorithms
Novel method for counterfactual learning in multivariate time series using genetic algorithms to uncover causal relationships and interventions.
3/3/2026
MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules
Presents MultiPUFFIN, a domain-constrained multimodal foundation model for molecular property prediction ensuring thermodynamic consistency across chemical space.
3/3/2026
Active Flow Matching
Introduces Active Flow Matching combining discrete diffusion/flow models with variational frameworks for black-box optimization without retraining.
3/3/2026
Knowledge without Wisdom: Measuring Misalignment between LLMs and Intended Impact
Evaluates performance misalignment between leading LLMs on out-of-distribution educational tasks, finding inter-model behaviors correlate higher than with human expert behaviors.
3/3/2026
Probabilistic Learning and Generation in Deep Sequence Models
Addresses uncertainty awareness in deep sequence models by integrating Bayesian methods with probabilistic learning, comparing approximate inference techniques.
3/3/2026
Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
Large-scale empirical study of AI grading on handwritten calculus work using OCR-conditioned LLMs with rubric-guided prompting for score and feedback generation.
3/3/2026
Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning
Proposes dual-learner framework combining fast learner and meta learner for continual RL, inspired by hippocampus-cortex interaction for knowledge transfer and integration.
3/3/2026
When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning
Investigates margin clamping effects on training variance in Contrastive Forward-Forward learning for Vision Transformers, addressing instability sources.
3/3/2026
Stabilizing Policy Optimization via Logits Convexity
Analyzes stability gap between supervised fine-tuning and RL in LLM training from gradient perspective, showing logits convexity role in stable optimization.
3/3/2026
Intent-Context Synergy Reinforcement Learning for Autonomous UAV Decision-Making in Air Combat
Proposes Intent-Context Synergy RL approach for autonomous UAV decision-making in contested environments, addressing trade-offs between mission efficiency and survivability.
3/3/2026
Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models
arXiv 2603.00975: Representation interference framework for selective unlearning in text-to-image diffusion models preserving quality.
3/3/2026
Compensation-free Machine Unlearning in Text-to-Image Diffusion Models by Eliminating the Mutual Information
arXiv 2603.00992: Machine unlearning method for diffusion models removing sensitive concepts via mutual information elimination.
3/3/2026
One-Token Verification for Reasoning Correctness Estimation
arXiv 2603.01025: One-token verification method for estimating correctness in LLM reasoning with reduced computational cost.
3/3/2026
Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift
arXiv 2603.01040: Fed-ADE for federated learning adaptation under distribution shifts without ground-truth labels.