4/6/2026
TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning
arXiv paper introducing TRACE, ML pipeline for detecting Internet routing changes using traceroute latency data with ensemble learning.
4/6/2026
Backdoor Attacks on Decentralised Post-Training
arXiv paper analyzing backdoor attacks on decentralized LLM post-training via pipeline parallelism, examining vulnerabilities from malicious participants.
4/6/2026
Photonic convolutional neural network with pre-trained in-situ training
arXiv paper proposing fully photonic convolutional neural network with pre-trained in-situ training to overcome CMOS energy bottlenecks.
4/6/2026
PlayGen-MoG: Framework for Diverse Multi-Agent Play Generation via Mixture-of-Gaussians Trajectory Prediction
PlayGen-MoG: Mixture-of-Gaussians framework for diverse multi-agent trajectory generation in team sports with spatial coordination.
4/6/2026
Guideline2Graph: Profile-Aware Multimodal Parsing for Executable Clinical Decision Graphs
Guideline2Graph: LLM/VLM-based parser converting multimodal clinical guidelines into executable decision graphs with cross-page control flow.
4/6/2026
Failing to Falsify: Evaluating and Mitigating Confirmation Bias in Language Models
Examination of confirmation bias in LLMs through rule-discovery tasks, evaluating and mitigating systematic reasoning failures.
4/6/2026
Optimal Projection-Free Adaptive SGD for Matrix Optimization
Projection-free adaptive SGD for matrix optimization achieving dimension-independent convergence without costly quadratic projections.
4/6/2026
Reinforcement Learning from Human Feedback: A Statistical Perspective
Statistical survey of RLHF for LLM alignment, examining noisy subjective feedback for reward models and policy optimization.
4/6/2026
Neural posterior estimation for scalable and accurate inverse parameter inference in Li-ion batteries
Neural posterior estimation for Bayesian parameter inference in Li-ion batteries using probabilistic calibration.
4/6/2026
AQVolt26: High-Temperature r$^2$SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries
AQVolt26: High-temperature halide dataset with r²SCAN calculations for training universal ML potentials for solid-state batteries.
4/6/2026
Interpretable Deep Reinforcement Learning for Element-level Bridge Life-cycle Optimization
Deep reinforcement learning for element-level bridge lifecycle optimization using condition state proportions.
4/6/2026
Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions?
Feature Attribution Stability Suite: Evaluates post-hoc attribution method stability under realistic input perturbations with improved metrics.
4/6/2026
Synapse: Evolving Job-Person Fit with Explainable Two-phase Retrieval and LLM-guided Genetic Resume Optimization
Synapse: LLM-guided two-phase retrieval and genetic algorithm optimization for job-person matching under information imbalance.
4/6/2026
Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation
Empirical study of confidence calibration and hallucination in vision-language models for medical VQA, spanning three model families.
4/6/2026
Contrastive Language-Colored Pointmap Pretraining for Unified 3D Scene Understanding
UniScene3D: Transformer-based 3D scene encoder jointly modeling appearance and geometry from multi-view colored pointmaps with CLIP alignment.
4/6/2026
Robust Learning with Optimal Error
Optimal error algorithms for adversarial learning using randomized hypotheses, improving deterministic hypothesis bounds by factor of 1/2.
4/6/2026
WSVD: Weighted Low-Rank Approximation for Fast and Efficient Execution of Low-Precision Vision-Language Models
WSVD: Weighted SVD technique for efficient low-precision execution of vision-language models with reduced computational burden.
4/6/2026
Understanding the Effects of Safety Unalignment on Large Language Models
Study examining safety alignment bypass methods in LLMs via jailbreak-tuning and weight orthogonalization, analyzing disabled safety guardrails.
4/6/2026
Learning interacting particle systems from unlabeled data
Trajectory-free self-test loss function for learning interacting particle system potentials from unlabeled discrete time-point data.
4/6/2026
Structure-Preserving Multi-View Embedding Using Gromov-Wasserstein Optimal Transport
Gromov-Wasserstein optimal transport methods for geometry-aware multi-view data embedding under heterogeneous geometries and nonlinear distortions.
4/6/2026
AutoVerifier: An Agentic Automated Verification Framework Using Large Language Models
AutoVerifier: LLM-based agentic framework automating end-to-end verification of technical claims across scientific literature without domain expertise required.
4/6/2026
Reinforcement Learning-based Knowledge Distillation with LLM-as-a-Judge
RL framework using LLM-as-judge for label-free knowledge distillation and reasoning improvement in small and large language models without ground truth labels.
4/6/2026
Transfer Learning for Meta-analysis Under Covariate Shift
Placebo-anchored transport framework for meta-analysis addressing covariate shift across randomized controlled trials.
4/6/2026
Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy
Systematic evaluation of LLM formal reasoning capabilities using Chomsky hierarchy and computation theory complexity metrics.
4/6/2026
MOMO: Mars Orbital Model Foundation Model for Mars Orbital Applications
MOMO: Foundation model merging multi-sensor Mars remote sensing data (HiRISE, CTX, THEMIS) using Equal Validation Loss alignment.
4/6/2026
State estimations and noise identifications with intermittent corrupted observations via Bayesian variational inference
Variational Bayesian adaptive Kalman filter for state estimation in sensor networks with packet dropouts and corrupted observations.
4/6/2026
Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces
Transfer learning approach for loan recovery prediction addressing data scarcity and distribution shifts across portfolio domains.
4/6/2026
Lipschitz bounds for integral kernels
Theoretical characterization of Lipschitz constants for kernel feature maps in positive definite kernels.
4/6/2026
Toward an Artificial General Teacher: Procedural Geometry Data Generation and Visual Grounding with Vision-Language Models
Procedural geometry data generation and visual grounding with vision-language models for Referring Image Segmentation in education.
4/6/2026
Split and Conquer Partial Deepfake Speech
Split-and-conquer framework for detecting manipulated speech regions via boundary detection and segment-level classification.
4/6/2026
Scalable Mean-Variance Portfolio Optimization via Subspace Embeddings and GPU-Friendly Nesterov-Accelerated Projected Gradient
GPU-accelerated solver combining randomized subspace embedding and Nesterov acceleration for large-scale portfolio optimization.
4/6/2026
Learning from Synthetic Data via Provenance-Based Input Gradient Guidance
Learning from synthetic data using provenance-based input gradient guidance to teach models discriminative regions.
4/6/2026
Inversion-Free Natural Gradient Descent on Riemannian Manifolds
Inversion-free stochastic natural gradient method for optimization on Riemannian manifolds with implicit parameter constraints.
4/6/2026
Learning Contractive Integral Operators with Fredholm Integral Neural Operators
Fredholm Integral Neural Operators framework for learning non-expansive integral operators with universal approximation proofs.
4/6/2026
SkillRT: Compiling Skills for Efficient Execution Everywhere
SkillRT: Compiler-inspired system treating LLM agent skills as code for consistent, efficient execution across diverse platforms.
4/6/2026
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
Theoretical characterization of Gaussian universality breakdown in high-dimensional convex empirical risk minimization under non-Gaussian data.
4/6/2026
The Compression Gap: Why Discrete Tokenization Limits Vision-Language-Action Model Scaling
Analysis of why discrete tokenization limits Vision-Language-Action model scaling; introduces Compression Gap information-theoretic principle.
4/6/2026
Learning the Signature of Memorization in Autoregressive Language Models
First transferable learned membership inference attack on fine-tuned LLMs using unlimited labeled data from fine-tuning process itself.
4/6/2026
PR3DICTR: A modular AI framework for medical 3D image-based detection and outcome prediction
PR3DICTR: PyTorch/MONAI-based open framework for 3D medical image classification and standardized deep learning model training.
4/6/2026
A Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security
Tsetlin Machine-based intrusion detection system for IoMT networks addressing cybersecurity vulnerabilities in medical device systems.
4/6/2026
Efficient Causal Graph Discovery Using Large Language Models
LLM framework for causal graph discovery using breadth-first search queries, reducing complexity from quadratic to linear query requirements.
4/6/2026
Output-Constrained Decision Trees
Methods for training constrained regression trees incorporating domain-specific output constraints using mixed-integer programming and other approaches.
4/6/2026
Supplementary Materials to Graph Convolutional Branch and Bound
Integration of neural networks into combinatorial optimization for NP-hard problems, learning heuristics and optimality scores via graph convolutional networks.
4/6/2026
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations
Amortized inference framework training single model to predict causal mechanisms across multiple datasets for out-of-distribution generalization.
4/6/2026
Distributional Statistics Restore Training Data Auditability in One-step Distilled Diffusion Models
Method for detecting unauthorized training data in one-step distilled diffusion models using distributional statistics instead of memorization detection.
4/6/2026
Zero-shot Concept Bottleneck Models
Zero-shot concept bottleneck models enabling interpretable predictions without target task training by leveraging pre-trained vision-language models.
4/6/2026
A Unified Approach to Analysis and Design of Denoising Markov Models
Mathematical framework unifying diffusion and flow-based generative models as denoising Markov processes with rigorous theoretical foundation.
4/6/2026
Accelerated Learning with Linear Temporal Logic using Differentiable Simulation
Integration of linear temporal logic specifications into RL using differentiable simulation for safe, correct-by-construction controller synthesis.
4/6/2026
Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring
Noise-robust exploration method for RL using learning progress monitoring to escape unlearnable noise sources with improved sample efficiency.
4/6/2026
ARMOR: High-Performance Semi-Structured Pruning via Adaptive Matrix Factorization
ARMOR: one-shot post-training pruning algorithm for LLMs achieving 2:4 semi-structured sparsity with minimal performance degradation for efficient deployment.