3/31/2026
Liquid Networks with Mixture Density Heads for Efficient Imitation Learning
Liquid neural networks with mixture density heads outperform diffusion policies in imitation learning with half the parameters and 2.4x lower prediction error.
3/31/2026
Conformalized Signal Temporal Logic Inference under Covariate Shift
Signal Temporal Logic inference learns interpretable rules for temporal behaviors using conformal prediction for uncertainty quantification under covariate shift.
3/31/2026
Dynamic resource matching in manufacturing using deep reinforcement learning
arXiv: Deep reinforcement learning for dynamic manufacturing resource matching and allocation.
3/31/2026
Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
arXiv: Generative model for valid 3D molecular structures using hierarchy-guided topology flows.
3/31/2026
Maximin Learning of Individualized Treatment Effect on Multi-Domain Outcomes
arXiv: DRIFT framework for individualized treatment effect estimation across multiple health domains.
3/31/2026
Spectral-Aware Text-to-Time Series Generation with Billion-Scale Multimodal Meteorological Data
Text-to-time-series generation framework for meteorological data using spectral-aware architecture with billion-scale dataset.
3/31/2026
ScoutAttention: Efficient KV Cache Offloading via Layer-Ahead CPU Pre-computation for LLM Inference
ScoutAttention optimizes LLM inference by pre-computing KV cache on CPU ahead of GPU execution to reduce memory constraints.
3/31/2026
Preconditioned Attention: Enhancing Efficiency in Transformers
Preconditioned attention mechanism addressing ill-conditioning in Transformer attention blocks for efficient training.
3/31/2026
GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph
GSR-GNN framework for efficient training of deep graph neural networks on large circuit graphs with memory optimization.
3/31/2026
Online Learning of Kalman Filtering: From Output to State Estimation
Online optimization framework for learning Kalman filtering in partially observed linear dynamical systems with unknown models.
3/31/2026
Hybrid Deep Learning with Temporal Data Augmentation for Accurate Remaining Useful Life Prediction of Lithium-Ion Batteries
CDFormer hybrid deep learning model for lithium-ion battery remaining useful life prediction with temporal data augmentation.
3/31/2026
Omni-Modal Dissonance Benchmark: Systematically Breaking Modality Consensus to Probe Robustness and Calibrated Abstention
OMD-Bench benchmark for testing multimodal model robustness by systematically breaking modality consensus.
3/31/2026
From Inference Routing to Agent Orchestration: Declarative Policy Compilation with Cross-Layer Verification
Semantic Router DSL for declarative LLM inference routing with content signal analysis, privacy policies, and audit traces.
3/31/2026
Scalable Maximum Entropy Population Synthesis via Persistent Contrastive Divergence
GibbsPCDSolver for scalable maximum entropy population synthesis from census data using persistent contrastive divergence.
3/31/2026
Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations
Spectrogram-Enhanced Multimodal Fusion using Vision Transformers for multivariate time series commodity price forecasting.
3/31/2026
Embedding Provenance in Computer Vision Datasets with JSON-LD
JSON-LD metadata framework for embedding provenance information in computer vision datasets.
3/31/2026
Active In-Context Learning for Tabular Foundation Models
Active learning approach for tabular foundation models using in-context learning to reduce cold-start labeling costs.
3/31/2026
Diagnosing Non-Markovian Observations in Reinforcement Learning via Prediction-Based Violation Scoring
Diagnostic method for detecting non-Markovian observation violations in reinforcement learning using prediction-based scoring.
3/31/2026
K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)
K-Means anomaly detection for microcontrollers with distributed model-sharing workflow via Distributed Internet of Learning.
3/31/2026
Conditional Factuality Controlled LLMs with Generalization Certificates via Conformal Sampling
Conditional Factuality Control framework for LLM hallucination control via conformal sampling with conditional coverage guarantees.
3/31/2026
The Geometry of Harmful Intent: Training-Free Anomaly Detection via Angular Deviation in LLM Residual Streams
LatentBiopsy: training-free method detecting harmful prompts by analyzing residual-stream activation geometry in LLMs.
3/31/2026
Kempe Swap K-Means: A Scalable Near-Optimal Solution for Semi-Supervised Clustering
K-Means clustering algorithm with Kempe swaps for semi-supervised constrained clustering under must-link and cannot-link constraints.
3/31/2026
The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks
Theoretical analysis of LayerNorm vs RMSNorm geometric constraints and their effect on neural network Bayesian complexity.
3/31/2026
GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
Image-to-CAD program synthesis using geometric feedback for bootstrapping alignment between visual and symbolic representations.
3/31/2026
FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies
Modular framework and taxonomy for reinforcement learning with diffusion and flow models as policy representations.
3/31/2026
TurboAngle: Near-Lossless KV Cache Compression via Uniform Angle Quantization
KV cache compression via uniform angle quantization in Fast Walsh-Hadamard domain with per-layer precision allocation.
3/31/2026
KV Cache Quantization for Self-Forcing Video Generation: A 33-Method Empirical Study
Empirical study of 33 KV cache quantization methods for self-forcing video generation with memory optimization.
3/31/2026
On Token's Dilemma: Dynamic MoE with Drift-Aware Token Assignment for Continual Learning of Large Vision Language Models
Mixture of Experts with drift-aware token routing for continual instruction tuning of large vision language models.
3/31/2026
Variational Learning of Fractional Posteriors
Variational learning approach for estimating fractional posteriors with applications to probabilistic modeling.
3/31/2026
Decomposing Discrimination: Causal Mediation Analysis for AI-Driven Credit Decisions
Causal mediation analysis framework using Pearl's methods to decompose discrimination in AI-driven credit decisions.
3/31/2026
Match or Replay: Self Imitating Proximal Policy Optimization
Self-imitating proximal policy optimization algorithm improving exploration efficiency in sparse reward reinforcement learning.
3/31/2026
Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization
Binary latent space protein fitness optimization using QUBO-based methods and pretrained protein language models.
3/31/2026
Visualization of Machine Learning Models through Their Spatial and Temporal Listeners
Model-centric visualization framework using spatial and temporal listeners to analyze ML model behaviors.
3/31/2026
Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs
Graph neural network method addressing oversquashing via cross-attentive cohesive subgraph embedding for long-range information.
3/31/2026
BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities
Federated learning framework for multimodal data with heterogeneous clients and missing modalities using block-wise approach.
3/31/2026
An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery
Spiking neural network architecture for energy-efficient predictive insulin delivery on wearable devices.
3/31/2026
On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry
Theoretical analysis of self-supervised pre-training using two-stage M-estimation and representation symmetry to improve bounds.
3/31/2026
Prototype-Aligned Federated Soft-Prompts for Continual Web Personalization
Federated soft-prompts framework for continual web personalization with privacy preservation and stability-plasticity control.
3/31/2026
CrossHGL: A Text-Free Foundation Model for Cross-Domain Heterogeneous Graph Learning
Heterogeneous graph representation learning foundation model for cross-domain transfer without textual attributes or domain-specific schemas.
3/31/2026
Optimizing Coverage and Difficulty in Reinforcement Learning for Quiz Composition
Reinforcement learning agents (DQN, SARSA, A2C/A3C) for automated quiz composition with topic coverage and difficulty optimization.
3/31/2026
Low-Rank Adaptation Reduces Catastrophic Forgetting in Sequential Transformer Encoder Fine-Tuning: Controlled Empirical Evidence and Frozen-Backbone Representation Probes
Empirical study of Low-Rank Adaptation (LoRA) in sequential fine-tuning of transformer encoders, analyzing catastrophic forgetting behavior.
3/31/2026
TMTE: Effective Multimodal Graph Learning with Task-aware Modality and Topology Co-evolution
Multimodal graph learning framework addressing topology quality issues in multimodal-attributed graphs through task-aware co-evolution.
3/31/2026
Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Training
DNNs for detecting smart contract vulnerabilities using contrastive learning and granular-ball training to handle noisy labeled datasets.
3/31/2026
What-If Explanations Over Time: Counterfactuals for Time Series Classification
Survey of counterfactual explanation algorithms for time series classification, covering instance-based, pattern-driven, and gradient-based methods.
3/31/2026
Distributed Online Submodular Maximization under Communication Delays: A Simultaneous Decision-Making Approach
Distributed online algorithm for multi-agent submodular maximization under communication delays for information-gathering in dynamic environments.
3/31/2026
RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
RG-TTA: Meta-controller for test-time adaptation in streaming time series forecasting that modulates adaptation intensity based on regime similarity.
3/31/2026
KVSculpt: KV Cache Compression as Distillation
KVSculpt: KV cache compression for long-context LLM inference treating compression as knowledge distillation, orthogonal to quantization and low-rank methods.
3/31/2026
Stability and Sensitivity Analysis of Relative Temporal-Difference Learning: Extended Version
Stability analysis of relative temporal-difference learning with linear function approximation, establishing convergence conditions when discount factor approaches one.
3/31/2026
Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
Primal-dual policy optimization algorithm for safe reinforcement learning in linear mixture CMDPs with adversarial rewards and unknown transitions.
3/31/2026
Spectral Signatures of Data Quality: Eigenvalue Tail Index as a Diagnostic for Label Noise in Neural Networks
Eigenvalue tail index of neural network weight matrices predicts test accuracy under label noise, achieving R^2=0.984 as diagnostic for data quality.