3/30/2026
GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration
Vision network for 2D-3D image-to-point-cloud registration using geometry-aware local alignment and structural synchronization.
3/30/2026
Preference-Aligned LoRA Merging: Preserving Subspace Coverage and Addressing Directional Anisotropy
Approach for merging multiple LoRA modules while preserving subspace coverage and addressing directional anisotropy to maintain task representation in general-purpose systems.
3/30/2026
Semi-structured multi-state delinquency model for mortgage default
Semi-structured discrete-time model combining additive predictors with neural networks for mortgage delinquency analysis and default prediction.
3/30/2026
SALMUBench: A Benchmark for Sensitive Association-Level Multimodal Unlearning
Benchmark for evaluating machine unlearning in multimodal models like CLIP, introducing SALMUBench with 60K persona-attribute associations for fine-grained forgetting evaluation.
3/30/2026
Label-Free Cross-Task LoRA Merging with Null-Space Compression
Method for merging independently fine-tuned LoRA adapters across heterogeneous tasks using null-space compression, addressing classification-regression task combinations.
3/30/2026
STN-GPR: A Singularity Tensor Network Framework for Efficient Option Pricing
Tensor-network surrogate for efficient option pricing in portfolio risk management using tensor-train approximation.
3/30/2026
Making Multi-Axis Models Robust to Multiplicative Noise: How, and Why?
Graph-learning algorithm (MED-MAGMA) for fitting Kronecker-sum-structured models with multiplicative noise in genomics applications.
3/30/2026
A Power-Weighted Noncentral Complex Gaussian Distribution
Power-weighted noncentral complex Gaussian distribution for signal processing and communications with non-Gaussian amplitude characteristics.
3/30/2026
Generative Score Inference for Multimodal Data
Generative approach for uncertainty quantification in multimodal supervised learning combining images and text data.
3/30/2026
Kantorovich--Kernel Neural Operators: Approximation Theory, Asymptotics, and Neural Network Interpretation
Theoretical analysis of Kantorovich-kernel neural network operators with density results, convergence estimates, and Korovkin theorems.
3/30/2026
Reconstructing Quantum Dot Charge Stability Diagrams with Diffusion Models
Diffusion models for reconstructing quantum dot charge stability diagrams to accelerate quantum processor characterization.
3/30/2026
Meta-Learned Adaptive Optimization for Robust Human Mesh Recovery with Uncertainty-Aware Parameter Updates
Meta-learning framework for human mesh recovery from images using optimization-friendly initializations and uncertainty-aware updates.
3/30/2026
UNIFERENCE: A Discrete Event Simulation Framework for Developing Distributed AI Models
UNIFERENCE: discrete-event simulation framework for developing and benchmarking distributed AI inference algorithms across heterogeneous devices and networks.
3/30/2026
Conditional Neural Bayes Ratio Estimation for Experimental Design Optimisation
Conditional Neural Bayes Ratio Estimation (cNBRE) for experimental design optimization in frontier physics, applied to 21-cm radio cosmology.
3/30/2026
Identifying Connectivity Distributions from Neural Dynamics Using Flows
Low-rank RNN approach using flows to infer neural connectivity structure from population recordings while addressing degeneracy in neural dynamics.
3/30/2026
AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese
AMALIA: fully open source LLM trained on high-quality European Portuguese data with native evaluation benchmark and improved pt-PT representation.
3/30/2026
ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs
ALBA: linguistically grounded benchmark for evaluating LLM performance on European Portuguese, addressing underrepresentation in existing benchmarks.
3/30/2026
From Synthetic Data to Real Restorations: Diffusion Model for Patient-specific Dental Crown Completion
ToothCraft: diffusion model for automated dental crown completion using synthetic training data and contextual generation from incomplete teeth.
3/30/2026
Sustainability Is Not Linear: Quantifying Performance, Energy, and Privacy Trade-offs in On-Device Intelligence
Experimental pipeline profiling energy consumption, latency, and quality trade-offs for deploying LLMs on edge devices with hardware constraints.
3/30/2026
Machine Learning Transferability for Malware Detection
Study evaluating ML feature compatibility and transferability across malware detection datasets under distribution shifts.
3/30/2026
PerceptionComp: A Video Benchmark for Complex Perception-Centric Reasoning
Video benchmark for complex perception reasoning requiring multiple temporally separated visual evidence pieces and compositional logic.
3/30/2026
Tunable Soft Equivariance with Guarantees
Framework for constructing soft equivariant computer vision models by projecting weights into designed subspaces with theoretical bounds.
3/30/2026
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients
Deep symbolic regression using policy gradients with complexity awareness for interpretable data-driven mathematical expression discovery.
3/30/2026
Nonmyopic Global Optimisation via Approximate Dynamic Programming
Approximate dynamic programming approach for global optimization of expensive black-box functions as alternative to Gaussian process Bayesian optimization.
3/30/2026
Projection-free Algorithms for Online Convex Optimization with Adversarial Constraints
Projection-free algorithms for online convex optimization with time-varying adversarial constraints and regret bounds.
3/30/2026
How iteration order influences convergence and stability in deep learning
Theoretical analysis of how iteration order affects convergence and stability in deep neural network training without learning rate schedules.
3/30/2026
Robust Predictive Modeling Under Unseen Data Distribution Shifts: A Methodological Commentary
Methodological commentary on robust predictive modeling under distribution shifts in real-world deployment scenarios.
3/30/2026
Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models
Task Tokens method adapts behavior foundation models to specific tasks via learnable tokens while preserving zero-shot generalization capabilities.
3/30/2026
FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation
FastCache accelerates Diffusion Transformer inference through learnable linear approximation and spatial-aware token selection for hidden-state caching.
3/30/2026
Defending Against Knowledge Poisoning Attacks During Retrieval-Augmented Generation
Defends RAG systems against knowledge poisoning attacks by detecting and mitigating adversarial text injections in external knowledge sources.
3/30/2026
Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images
Masked training approach for robust arrhythmia detection from digitalized ECG images with temporal asynchrony and missing signal segments.
3/30/2026
PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning
PepThink-R1 integrates LLMs with chain-of-thought supervised fine-tuning and reinforcement learning for interpretable cyclic peptide design optimization.
3/30/2026
MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models
Generative model for molecular dynamics trajectories using Markov State Models to accelerate computational protein simulations.
3/30/2026
Large Language Models Can Perform Automatic Modulation Classification via Discretized Self-supervised Candidate Retrieval
LLMs perform automatic wireless modulation classification via discretized self-supervised candidate retrieval, avoiding distribution shift issues of supervised models.
3/30/2026
Activation Steering with a Feedback Controller
Control-theoretic framework for LLM activation steering with feedback controllers, connecting empirical steering methods to proportional control theory for safety alignment.
3/30/2026
NeST-BO: Fast Local Bayesian Optimization via Newton-Step Targeting of Gradient and Hessian Information
NeST-BO proposes Newton-step targeting Bayesian optimization using Gaussian processes to learn gradient and Hessian information for expensive black-box problems.
3/30/2026
Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?
Analyzes cryptanalytic model extraction attacks on ReLU-based DNNs with hard-label oracle access and polynomial-time complexity.
3/30/2026
Route Experts by Sequence, not by Token
Sequence-level TopK (SeqTopK) improves Mixture-of-Experts routing in LLMs by adapting expert assignment per sequence rather than per token without retraining.
3/30/2026
Cascading Bandits With Feedback
Cascading Bandits analyzes decision-making policies for edge inference with multiple models, providing theoretical regret guarantees for Explore-then-Commit and Thompson Sampling approaches.
3/30/2026
LiteCache: A Query Similarity-Driven, GPU-Centric KVCache Subsystem for Efficient LLM Inference
LiteCache optimizes KVCache memory management for LLM inference using GPU-centric query similarity-driven approach to reduce memory overhead and improve CUDA Graph execution.
3/30/2026
ReBaPL: Repulsive Bayesian Prompt Learning
Repulsive Bayesian Prompt Learning addresses overfitting in prompt learning for foundation models using Bayesian inference framework for improved out-of-distribution generalization.
3/30/2026
Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
Balanced Fine-Tuning aligns LLMs with biomedical knowledge through confidence-weighted token-level optimization and adaptive reward mechanisms.
3/30/2026
FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning
FedRE proposes a representation entanglement framework enabling federated learning across clients with heterogeneous model architectures and data.
3/30/2026
SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations
SonicMoE optimizes Mixture of Experts inference through IO-aware and tile-aware techniques for high-granularity, sparse MoE language models.
3/30/2026
PathFinder: Advancing Path Loss Prediction for Single-to-Multi-Transmitter Scenario
Deep learning approach for radio path loss prediction in 5G networks with improved generalization across multi-transmitter scenarios and distribution shifts.
3/30/2026
Concurrent training methods for Kolmogorov-Arnold networks: Disjoint datasets and FPGA implementation
Concurrent training enhancements for Kolmogorov-Arnold networks using Newton-Kaczmarz method with FPGA implementation for improved efficiency.
3/30/2026
The Dual-State Architecture for Reliable LLM Agents
Dual-State Action Pair (DSAP) primitive couples stochastic LLM generation with deterministic verification for reliable code generation agents.
3/30/2026
Mobility-Assisted Decentralized Federated Learning: Convergence Analysis and A Data-Driven Approach
Analyzes decentralized federated learning convergence with user mobility and data heterogeneity in next-gen wireless networks.
3/30/2026
Revisiting Diffusion Model Predictions Through Dimensionality
Provides theoretical framework explaining why diffusion models prefer direct data prediction over noise/velocity prediction in high-dimensional settings.
3/30/2026
Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration
Extends Puzzle neural architecture search to reasoning LLMs, producing gpt-oss-puzzle-88B through MoE expert pruning and inference optimization.