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.
4/3/2026
Generalization Bounds and Statistical Guarantees for Multi-Task and Multiple Operator Learning with MNO Networks
Statistical analysis of multi-task and multiple operator learning architectures with generalization bounds and theoretical guarantees.
4/3/2026
World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
Self-improving world models using forward-inverse asymmetry to improve robustness across suboptimal actions for policy evaluation and planning.
4/3/2026
Apriel-Reasoner: RL Post-Training for General-Purpose and Efficient Reasoning
RL post-training framework for building general-purpose reasoning models across diverse domains with verifiable rewards, addressing multi-domain optimization challenges.
4/3/2026
Feature Weighting Improves Pool-Based Sequential Active Learning for Regression
Active learning method using feature weighting for regression tasks to optimize sample selection from unlabeled pools under budget constraints.
4/3/2026
Ouroboros: Dynamic Weight Generation for Recursive Transformers via Input-Conditioned LoRA Modulation
ArXiv paper on dynamic weight generation for recursive transformers using input-conditioned LoRA modulation controller.
4/3/2026
AA-SVD : Anchored and Adaptive SVD for Large Language Model Compression
ArXiv paper on fast SVD-based compression for large language models without retraining, addressing distribution shifts.
4/3/2026
Application of parametric Shallow Recurrent Decoder Network to magnetohydrodynamic flows in liquid metal blankets of fusion reactors
ArXiv paper applying shallow recurrent decoder networks to magnetohydrodynamic flow modeling in fusion reactors.
4/3/2026
Neural network methods for two-dimensional finite-source reflector design
ArXiv paper using neural networks to solve inverse problem of designing reflectors for light distribution.
4/3/2026
LEO: Graph Attention Network based Hybrid Multi Sensor Extended Object Fusion and Tracking for Autonomous Driving Applications
ArXiv paper on graph attention network for multi-sensor object fusion and tracking in autonomous driving.
4/3/2026
Universal Hypernetworks for Arbitrary Models
ArXiv paper introducing Universal Hypernetworks that generate weights for arbitrary model architectures using descriptors.
4/3/2026
Smoothing the Landscape: Causal Structure Learning via Diffusion Denoising Objectives
ArXiv paper applying diffusion denoising objectives to causal structure learning from observational data.
4/3/2026
Model-Based Reinforcement Learning for Control under Time-Varying Dynamics
ArXiv paper on model-based reinforcement learning for control systems with time-varying dynamics.
4/3/2026
SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization
ArXiv paper on in-context agentic reinforcement learning enabling LLM agents to internalize skills at inference time.
4/3/2026
Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
ArXiv paper on lightweight diffusion transformer for crystal structure generation using subatomic tokenization.
4/3/2026
Unifying Group-Relative and Self-Distillation Policy Optimization via Sample Routing
ArXiv paper unifying group-relative and self-distillation policy optimization for LLM post-training with improved credit assignment.
4/3/2026
Taming the Exponential: A Fast Softmax Surrogate for Integer-Native Edge Inference
ArXiv paper proposing Head-Calibrated Clipped-Linear Softmax as efficient surrogate for attention softmax in edge inference.
4/3/2026
go-$m$HC: Direct Parameterization of Manifold-Constrained Hyper-Connections via Generalized Orthostochastic Matrices
ArXiv paper on exact parameterization of doubly stochastic matrices for learned mixing in neural networks.
4/3/2026
Batched Contextual Reinforcement: A Task-Scaling Law for Efficient Reasoning
Single-stage training paradigm for efficient LLM reasoning that reduces token consumption in chain-of-thought without degrading quality.
4/3/2026
Interpretable Battery Aging without Extra Tests via Neural-Assisted Physics-based Modelling
Neural-assisted physics-based model for interpretable battery aging prediction via 2D aging fingerprints without additional diagnostics.
4/3/2026
A Learning-Based Cooperative Coevolution Framework for Heterogeneous Large-Scale Global Optimization
Learning-based cooperative coevolution framework addressing heterogeneous large-scale global optimization via adaptive low-dimensional optimizers.