3/31/2026
MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations
MR-CDM framework for multi-resolution time series generation using hierarchical decomposition and diffusion models.
3/31/2026
Corruption-robust Offline Multi-agent Reinforcement Learning From Human Feedback
Study on robustness against data corruption in offline multi-agent reinforcement learning from human feedback.
3/31/2026
Pre-Deployment Complexity Estimation for Federated Perception Systems
Framework for estimating learning complexity and communication costs in federated learning systems before deployment.
3/31/2026
FI-KAN: Fractal Interpolation Kolmogorov-Arnold Networks
FI-KAN introduces fractal interpolation function bases into Kolmogorov-Arnold Networks for improved multi-scale function approximation.
3/31/2026
OptINC: Optical In-Network-Computing for Scalable Distributed Learning
arXiv paper proposing optical in-network computing to reduce communication overhead in distributed machine learning systems.
3/31/2026
LIBERO-Para: A Diagnostic Benchmark and Metrics for Paraphrase Robustness in VLA Models
arXiv paper introducing LIBERO-Para benchmark to evaluate robustness of Vision-Language-Action models to paraphrased instructions in robotic tasks.
3/31/2026
Taming the Instability: A Robust Second-Order Optimizer for Federated Learning over Non-IID Data
arXiv paper proposing FedRCO, a second-order optimization framework for federated learning with improved stability under non-IID data.
3/31/2026
FairGC: Fairness-aware Graph Condensation
arXiv paper addressing fairness issues in graph condensation, preventing amplification of demographic biases during dataset compression.
3/31/2026
Physics-Informed Neural Networks for Predicting Hydrogen Sorption in Geological Formations: Thermodynamically Constrained Deep Learning Integrating Classical Adsorption Theory
arXiv paper using physics-informed neural networks to predict hydrogen sorption in geological formations with thermodynamic constraints.
3/31/2026
Machine Learning-Assisted High-Dimensional Matrix Estimation
arXiv paper integrating learning-based optimization with classical statistical methods for efficient high-dimensional matrix estimation.
3/31/2026
Critic-Free Deep Reinforcement Learning for Maritime Coverage Path Planning on Irregular Hexagonal Grids
arXiv paper applying deep reinforcement learning to maritime coverage path planning on irregular hexagonal grids.
3/31/2026
Label-efficient Training Updates for Malware Detection over Time
arXiv paper addressing label-efficient retraining of malware detection models under distribution drift in real-world settings.
3/31/2026
Mixture-Model Preference Learning for Many-Objective Bayesian Optimization
arXiv paper on Bayesian framework for preference learning in many-objective optimization using mixture models of latent preference archetypes.
3/31/2026
Evolutionary Discovery of Reinforcement Learning Algorithms via Large Language Models
arXiv paper presenting evolutionary framework using LLMs to discover novel reinforcement learning algorithms by searching over executable update rules.
3/31/2026
KGroups: A Versatile Univariate Max-Relevance Min-Redundancy Feature Selection Algorithm for High-dimensional Biological Data
arXiv paper introducing KGroups, a feature selection algorithm for high-dimensional biological data using max-relevance min-redundancy criteria.
3/31/2026
IsoQuant: Hardware-Aligned SO(4) Isoclinic Rotations for LLM KV Cache Compression
IsoQuant uses quaternion algebra and isoclinic rotations for efficient LLM KV cache compression with hardware-aligned blockwise operations.
3/31/2026
FeDMRA: Federated Incremental Learning with Dynamic Memory Replay Allocation
FeDMRA addresses federated class-incremental learning with dynamic memory replay for non-IID distributed healthcare data.
3/31/2026
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention
HISA improves efficiency of token-level sparse attention mechanisms through hierarchical indexing, reducing O(L²) bottleneck.
3/31/2026
The Unreasonable Effectiveness of Scaling Laws in AI
Analysis of scaling laws in AI across model families, explaining their predictive power and universal effectiveness in training loss reduction.
3/31/2026
Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework
Interpretable machine learning framework for detecting low left ventricular ejection fraction from ECG data using predictor-driven approach.
3/31/2026
CirrusBench: Evaluating LLM-based Agents Beyond Correctness in Real-World Cloud Service Environments
CirrusBench evaluates LLM-based agents in real-world cloud service environments beyond correctness, measuring robustness and efficiency.
3/31/2026
Unrestrained Simplex Denoising for Discrete Data. A Non-Markovian Approach Applied to Graph Generation
Simplex denoising framework for discrete generative modeling using non-Markovian noising scheme, applied to graph generation.
3/31/2026
Learning Partial Action Replacement in Offline MARL
Offline multi-agent reinforcement learning approach using Partial Action Replacement to handle exponential joint action space growth.
3/31/2026
ChemCLIP: Bridging Organic and Inorganic Anticancer Compounds Through Contrastive Learning
ChemCLIP uses contrastive learning to bridge organic and inorganic anticancer compound discovery by enabling knowledge transfer across chemical domains.
3/31/2026
Physics-Informed Framework for Impact Identification in Aerospace Composites
Physics-informed impact identification framework combining observational and inductive biases for aerospace composite damage detection.
3/31/2026
Position: Explainable AI is Causality in Disguise
Position paper arguing explainable AI fundamentally relies on causal inference rather than diverse disconnected XAI methods.
3/31/2026
LACE: Loss-Adaptive Capacity Expansion for Continual Learning
LACE mechanism for continual learning that adaptively expands model capacity during training based on loss signal monitoring.
3/31/2026
Information-Theoretic Limits of Safety Verification for Self-Improving Systems
Information-theoretic analysis of safety verification impossibility for self-improving systems balancing bounded risk with unbounded utility.
3/31/2026
Mitigating Backdoor Attacks in Federated Learning Using PPA and MiniMax Game Theory
Federated learning defense using PPA and game theory minimax approaches against backdoor attacks from malicious clients.
3/31/2026
AMIGO: Agentic Multi-Image Grounding Oracle Benchmark
AMIGO benchmark for evaluating agentic vision-language models on long-horizon multi-image grounding tasks through sequential attribute-focused queries.
3/31/2026
FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning
FL-PBM method for detecting and mitigating backdoor attacks in federated learning during pre-training phases.
3/31/2026
Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation
PACE system for backpropagation-free test-time adaptation by optimizing normalization layer parameters using covariance matrix approaches.
3/31/2026
GPU-Accelerated Optimization of Transformer-Based Neural Networks for Real-Time Inference
GPU-accelerated TensorRT inference pipeline for BERT and GPT-2 with mixed-precision optimization achieving 64.4x CPU speedup.
3/31/2026
Stepwise Credit Assignment for GRPO on Flow-Matching Models
Stepwise credit assignment method for GRPO on flow models that differentiates early composition steps from late detail-refinement steps.
3/31/2026
See it to Place it: Evolving Macro Placements with Vision-Language Models
VeoPlace uses vision-language models for chip floorplanning macro placement by leveraging VLM spatial reasoning abilities to complement learning-based approaches.
3/31/2026
Expectation Error Bounds for Transfer Learning in Linear Regression and Linear Neural Networks
Theoretical analysis of transfer learning in linear regression and neural networks with closed-form generalization error bounds.
3/31/2026
Rethinking Language Model Scaling under Transferable Hypersphere Optimization
HyperP introduces hypersphere parameterization for language model scaling with improved training stability compared to first-order optimizer approaches.
3/31/2026
Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation
Analysis of why linear probes and sparse autoencoders fail at compositional generalization under superposition, proposing iterative coding alternatives.
3/31/2026
Temporal Credit Is Free
Research on recurrent network training using temporal credit through hidden states without Jacobian propagation, addressing gradient normalization in online adaptation.
3/31/2026
SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs
SimulCost benchmark evaluates LLM agents on physics simulation tasks with cost-aware metrics, accounting for simulation time and experimental resource usage beyond token costs.
3/31/2026
ReCQR: Incorporating conversational query rewriting to improve Multimodal Image Retrieval
Conversational query rewriting approach for multimodal image retrieval with multi-turn dialogue dataset.
3/31/2026
GeoBlock: Inferring Block Granularity from Dependency Geometry in Diffusion Language Models
GeoBlock infers optimal block sizes for diffusion language models by analyzing token dependency geometry to enable efficient parallel decoding.
3/31/2026
Contextual Graph Representations for Task-Driven 3D Perception and Planning
Method for extracting task-relevant contextual representations from 3D scene graphs for robot planning and perception.
3/31/2026
EVNextTrade: Learning-to-Rank-Based Recommendation of Next Charging Nodes for EV-EV Energy Trading
Learning-to-rank system for recommending charging nodes in peer-to-peer EV energy trading networks.
3/31/2026
Complementarity-Preserving Generative Theory for Multimodal ECG Synthesis: A Quantum-Inspired Approach
Generative theory for synthesizing physiologically consistent multimodal ECG data using quantum-inspired approach.
3/31/2026
EMPD: An Event-based Multimodal Physiological Dataset for Remote Pulse Wave Detection
Benchmark dataset for remote pulse wave detection using event cameras and multimodal physiological sensing.
3/31/2026
PI-Mamba: Linear-Time Protein Backbone Generation via Spectrally Initialized Flow Matching
Physics-informed generative model using Mamba architecture for efficient protein backbone design with linear-time complexity and improved structural fidelity.
3/31/2026
FEMBA on the Edge: Physiologically-Aware Pre-Training, Quantization, and Deployment of a Bidirectional Mamba EEG Foundation Model on an Ultra-low Power Microcontroller
FEMBA: bidirectional Mamba state-space model pre-trained on 21k hours EEG with physiologically-aware objectives for microcontroller deployment.
3/31/2026
Stress Classification from ECG Signals Using Vision Transformer
Vision Transformer applied to stress classification from ECG signals using STFT spectrograms for physiological signal analysis.
3/31/2026
Mixture of Experts with Soft Nearest Neighbor Loss: Resolving Expert Collapse via Representation Disentanglement
Enhanced mixture-of-experts architecture using soft nearest neighbor loss to prevent expert collapse and redundant representations.