4/3/2026
Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method
Sven optimization algorithm exploiting natural loss decomposition using Moore-Penrose pseudoinverse for efficient neural network training.
4/3/2026
Forecasting Supply Chain Disruptions with Foresight Learning
Framework training LLMs to forecast supply chain disruptions using calibrated probabilistic forecasts from disruption outcomes.
4/3/2026
UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression
UQ-SHRED adds uncertainty quantification to shallow recurrent decoder networks for sparse spatiotemporal reconstruction.
4/3/2026
An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis
Online machine learning framework for multi-resolution energy system design optimization and performance analysis.
4/3/2026
JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics
JetPrism diagnoses convergence issues in Conditional Flow Matching for physics simulations and inverse problems.
4/3/2026
Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling
Distributed graph modeling approach for detecting money laundering transaction patterns at scale.
4/3/2026
Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial
Tutorial on Bayesian Optimization as a principled framework for automating scientific discovery using surrogate models.
4/3/2026
Model Merging via Data-Free Covariance Estimation
Principled layer-wise optimization approach for model merging via data-free covariance estimation without task-specific training.
4/3/2026
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
SECURE framework addressing robustness issues in deep learning models for autonomous driving collision prediction.
4/3/2026
Massively Parallel Exact Inference for Hawkes Processes
GPU-accelerated inference algorithm for multivariate Hawkes processes achieving O(N) complexity with parallelization.
4/3/2026
Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
Novel Langevin-based algorithm for adaptive inverse reinforcement learning using Malliavin calculus for gradient estimation.
4/3/2026
PI-JEPA: Label-Free Surrogate Pretraining for Coupled Multiphysics Simulation via Operator-Split Latent Prediction
PI-JEPA: Physics-informed surrogate model for multiphysics simulation exploiting unlabeled parameter fields via latent prediction.
4/3/2026
Residuals-based Offline Reinforcement Learning
Residuals-based offline reinforcement learning approach for high-stakes applications with restrictive data coverage assumptions.
4/3/2026
Benchmark Problems and Benchmark Datasets for the evaluation of Machine and Deep Learning methods on Photoplethysmography signals: the D4 report from the QUMPHY project
Benchmark datasets and evaluation protocols for machine learning methods on photoplethysmography medical signals.
4/3/2026
Test-Time Scaling Makes Overtraining Compute-Optimal
Train-to-Test scaling laws optimizing model size, training tokens, and inference samples jointly for compute-optimal LLM deployment.
4/3/2026
When Reward Hacking Rebounds: Understanding and Mitigating It with Representation-Level Signals
Study of reward hacking in LLM RL showing reproducible failure patterns and mitigation strategies using representation-level signals.
4/3/2026
DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data
Hierarchical RL framework for privacy-preserving synthetic clinical data generation combining LLMs with structured learning.
4/3/2026
CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe
CuTeGen: LLM-based agentic framework for automated generation and optimization of high-performance GPU kernels using CuTe abstraction.
4/3/2026
Matching Accuracy, Different Geometry: Evolution Strategies vs GRPO in LLM Post-Training
Comparative study of Evolution Strategies vs GRPO for LLM post-training showing ES achieves comparable accuracy with different parameter geometry.
4/3/2026
Beyond Logit Adjustment: A Residual Decomposition Framework for Long-Tailed Reranking
Residual decomposition framework for improving classifier performance on long-tailed datasets beyond standard logit adjustment.
4/3/2026
Learning ECG Image Representations via Dual Physiological-Aware Alignments
Self-supervised framework for learning clinical ECG image representations without access to raw signal recordings.
4/3/2026
ZEUS: Accelerating Diffusion Models with Only Second-Order Predictor
ZEUS: Training-free acceleration method for diffusion models using second-order predictors to reduce sampling steps.
4/3/2026
Care-Conditioned Neuromodulation for Autonomy-Preserving Supportive Dialogue Agents
Care-Conditioned Neuromodulation framework for LLM-based dialogue agents that balances helpfulness with user autonomy preservation.
4/3/2026
Optimizing EEG Graph Structure for Seizure Detection: An Information Bottleneck and Self-Supervised Learning Approach
EEG seizure detection method using graph neural networks with self-supervised learning and information bottleneck principles.
4/3/2026
Learning from the Right Rollouts: Data Attribution for PPO-based LLM Post-Training
Influence-Guided PPO framework for LLM post-training that filters noisy rollouts using data attribution to improve training efficiency.
4/3/2026
Training In-Context and In-Weights Mixtures Via Contrastive Context Sampling
Research on training LLMs to develop both in-context and in-weights learning capabilities simultaneously via contrastive context sampling.
4/3/2026
Pseudo-Quantized Actor-Critic Algorithm for Robustness to Noisy Temporal Difference Error
Novel reinforcement learning algorithm addressing noisy temporal difference errors in deep RL through pseudo-quantization methods.
4/3/2026
Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models
arXiv paper on expert-choice routing for diffusion language models. Deterministic load balancing improves throughput and convergence vs token-choice.
4/3/2026
CRIT: Graph-Based Automatic Data Synthesis to Enhance Cross-Modal Multi-Hop Reasoning
arXiv paper on CRIT, graph-based automatic data synthesis for cross-modal multi-hop reasoning. Generates complementary image-text data.
4/3/2026
Label Shift Estimation With Incremental Prior Update
arXiv paper on label shift estimation with incremental prior updates. Addresses distribution mismatch between training and deployment.
4/3/2026
Coupled Query-Key Dynamics for Attention
arXiv paper on coupled query-key dynamics for scaled dot-product attention. Improves language modeling perplexity by 6-7% on WikiText-103.
4/3/2026
MiCA Learns More Knowledge Than LoRA and Full Fine-Tuning
arXiv paper introducing MiCA, parameter-efficient LLM fine-tuning method adapting minor singular vector subspaces. Outperforms LoRA on knowledge retention.
4/3/2026
Transformer self-attention encoder-decoder with multimodal deep learning for response time series forecasting and digital twin support in wind structural health monitoring
arXiv paper on transformer encoder-decoder with multimodal learning for wind structural health monitoring and digital twins.
4/3/2026
MATA-Former & SIICU: Semantic Aware Temporal Alignment for High-Fidelity ICU Risk Prediction
arXiv paper on MATA-Former for ICU risk prediction using semantic-aware temporal alignment. Clinical-logic-aligned transformer architecture.
4/3/2026
Koopman-Based Nonlinear Identification and Adaptive Control of a Turbofan Engine
arXiv paper applying Koopman operator methods for multivariable control of turbofan engines. Meta-heuristic extended dynamic mode decomposition.
4/3/2026
DDCL: Deep Dual Competitive Learning: A Differentiable End-to-End Framework for Unsupervised Prototype-Based Representation Learning
arXiv paper on DDCL, differentiable end-to-end framework for unsupervised prototype-based representation learning. Integrates feature learning with clustering.
4/3/2026
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
arXiv paper proposing FourierMoE for parameter-efficient LLM fine-tuning in multi-task settings. Mixture-of-experts approach addressing task interference.
4/3/2026
Bridging Deep Learning and Integer Linear Programming: A Predictive-to-Prescriptive Framework for Supply Chain Analytics
arXiv paper integrating deep learning forecasting with integer linear programming for supply chain analytics. Three-stage framework on 180K transactions.
4/3/2026
Graph Neural Operator Towards Edge Deployability and Portability for Sparse-to-Dense, Real-Time Virtual Sensing on Irregular Grids
arXiv paper on graph neural operators for real-time virtual sensing on irregular grids with edge deployment. Addresses sparse-to-dense field inference.
4/3/2026
Physics Informed Reinforcement Learning with Gibbs Priors for Topology Control in Power Grids
arXiv paper combining reinforcement learning with physics-informed priors (Gibbs) for power grid topology control. Semi-Markov framework.
4/3/2026
CANDI: Curated Test-Time Adaptation for Multivariate Time-Series Anomaly Detection Under Distribution Shift
arXiv paper on test-time adaptation for multivariate time-series anomaly detection under distribution shift. Curated adaptation framework (CANDI).
4/3/2026
Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
arXiv paper introducing diffusion-based posterior sampling for uncertainty quantification in industrial data-driven models. Addresses safety-critical applications.
4/3/2026
Robust Graph Representation Learning via Adaptive Spectral Contrast
arXiv paper on spectral graph contrastive learning addressing high-frequency signal variance in heterophilic graphs. Theoretical analysis with regret bounds.
4/3/2026
DDCL-INCRT: A Self-Organising Transformer with Hierarchical Prototype Structure (Theoretical Foundations)
Self-organising transformer with hierarchical prototype structure that automatically determines optimal architecture dimensions (heads, depth, width) during training.
4/3/2026
LI-DSN: A Layer-wise Interactive Dual-Stream Network for EEG Decoding
Layer-wise Interactive Dual-Stream Network architecture for EEG decoding in brain-computer interfaces with improved temporal-spatial feature fusion.
4/3/2026
Enhancing the Reliability of Medical AI through Expert-guided Uncertainty Modeling
Expert-guided uncertainty modeling for medical AI systems to improve reliability and enable human experts to prioritize high-risk diagnostic cases.
4/3/2026
The Rank and Gradient Lost in Non-stationarity: Sample Weight Decay for Mitigating Plasticity Loss in Reinforcement Learning
Theoretical analysis of plasticity loss in deep reinforcement learning due to non-stationarity, proposing sample weight decay mitigation technique.
4/3/2026
PAC-Bayesian Reward-Certified Outcome Weighted Learning
PAC-Bayesian framework for outcome weighted learning that incorporates reward uncertainty into policy selection with finite-sample guarantees.
4/3/2026
annbatch unlocks terabyte-scale training of biological data in anndata
annbatch: Mini-batch loader for terabyte-scale biological data training in anndata format, addressing memory bottlenecks in ML pipelines for bioinformatics.
4/3/2026
Learn by Surprise, Commit by Proof
LSCP: Self-gated post-training framework for autonomous knowledge acquisition using self-generated Q&A chains and adaptive learning rates based on model conviction.