2/19/2026
Explainability for Fault Detection System in Chemical Processes
Comparison of SHAP and Integrated Gradients for explaining LSTM fault detection in chemical processes.
2/19/2026
Optical Inversion and Spectral Unmixing of Spectroscopic Photoacoustic Images with Physics-Informed Neural Networks
Physics-informed neural networks for optical inversion and spectral unmixing in photoacoustic imaging.
2/19/2026
Improved Bounds for Reward-Agnostic and Reward-Free Exploration
Theoretical analysis of reward-free and reward-agnostic exploration in MDPs with improved regret bounds.
2/19/2026
Easy Data Unlearning Bench
Unified benchmarking suite for evaluating machine unlearning algorithms with KLoM metric and precomputed model ensembles.
2/19/2026
Learning with Locally Private Examples by Inverse Weierstrass Private Stochastic Gradient Descent
Novel bias-correction method using Weierstrass transform for data released under local differential privacy in binary classification.
2/19/2026
Intra-Fairness Dynamics: The Bias Spillover Effect in Targeted LLM Alignment
Studies bias spillover in LLM fairness alignment, showing how single-attribute debiasing can worsen disparities in other dimensions.
2/19/2026
Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGA
FPGA implementation of event-graph neural networks for neuromorphic audio processing with low latency and energy efficiency.
2/19/2026
GICDM: Mitigating Hubness for Reliable Distance-Based Generative Model Evaluation
GICDM corrects hubness bias in high-dimensional embedding spaces for more reliable generative model evaluation metrics.
2/19/2026
Beyond SGD, Without SVD: Proximal Subspace Iteration LoRA with Diagonal Fractional K-FAC
LoRSum improves LoRA fine-tuning efficiency using proximal subspace iteration with diagonal K-FAC, reducing memory overhead.
2/19/2026
HPMixer: Hierarchical Patching for Multivariate Time Series Forecasting
Proposes HPMixer for multivariate time series forecasting using hierarchical patching to model periodic patterns and residuals.
2/19/2026
Synthesis and Verification of Transformer Programs
Develops verification techniques for C-RASP language capturing transformer-expressible concepts using model checkers and SMT-solvers.
2/19/2026
Fast and Scalable Analytical Diffusion
Addresses scalability of analytical diffusion models by reducing dataset scanning overhead at each timestep in generative modeling.
2/19/2026
Interpretability-by-Design with Accurate Locally Additive Models and Conditional Feature Effects
Proposes conditionally additive local models balancing interpretability of GAMs with accuracy by adding conditional feature interactions.
2/19/2026
Small molecule retrieval from tandem mass spectrometry: what are we optimizing for?
Examines deep learning approaches for identifying small molecules from tandem mass spectrometry using molecular fingerprint prediction.
2/19/2026
Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study
Compares reinforcement learning training regimes for parameterized quantum state preparation with continuous rotations.
2/19/2026
Capacity-constrained demand response in smart grids using deep reinforcement learning
Applies deep reinforcement learning to capacity-constrained demand response for smart grid management and congestion prevention.
2/19/2026
FEKAN: Feature-Enriched Kolmogorov-Arnold Networks
Introduces FEKAN, feature-enriched Kolmogorov-Arnold networks with improved scalability and convergence over existing KAN variants.
2/19/2026
Transfer Learning of Linear Regression with Multiple Pretrained Models: Benefiting from More Pretrained Models via Overparameterization Debiasing
Studies transfer learning for linear regression using multiple overparameterized pretrained models with debiasing.
2/19/2026
Vulnerability Analysis of Safe Reinforcement Learning via Inverse Constrained Reinforcement Learning
Analyzes vulnerabilities of safe reinforcement learning via inverse constrained RL without requiring policy gradient access.
2/19/2026
RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
Proposes RIDER, reinforcement learning-guided diffusion approach for inverse design of 3D RNA structures.
2/19/2026
Illustration of Barren Plateaus in Quantum Computing
Investigates barren plateau phenomenon in variational quantum circuits with parameter sharing for quantum machine learning.
2/19/2026
A Scalable Approach to Solving Simulation-Based Network Security Games
Introduces MetaDOAR meta-controller augmenting double oracle paradigm with filtering and caching for multi-agent RL on cyber networks.
2/19/2026
Steering diffusion models with quadratic rewards: a fine-grained analysis
Provides fine-grained analysis of steering diffusion models with quadratic rewards at inference time for downstream tasks.
2/19/2026
MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
Develops gradient boosting models for urban demand forecasting in intelligent transportation systems.
2/19/2026
AIFL: A Global Daily Streamflow Forecasting Model Using Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS
Proposes LSTM model pretrained on ERA5-Land reanalysis and finetuned on IFS for global streamflow forecasting.
2/19/2026
Sequential Membership Inference Attacks
Develops sequential membership inference attacks exploiting model dynamics across multiple updates for privacy auditing.
2/19/2026
Predicting The Cop Number Using Machine Learning
Applies machine learning to predict cop number in pursuit evasion graph game, addressing computational complexity.
2/19/2026
A Systematic Evaluation of Sample-Level Tokenization Strategies for MEG Foundation Models
Systematically evaluates tokenization strategies for foundation models applied to MEG neuroimaging time series data.
2/19/2026
Almost Sure Convergence of Differential Temporal Difference Learning for Average Reward Markov Decision Processes
Proves almost sure convergence of differential temporal difference learning for average reward reinforcement learning.
2/19/2026
Optimizer choice matters for the emergence of Neural Collapse
Analyzes role of optimizer choice in emergence of neural collapse patterns during deep neural network training.
2/19/2026
Factorization Machine with Quadratic-Optimization Annealing for RNA Inverse Folding and Evaluation of Binary-Integer Encoding and Nucleotide Assignment
Applies factorization machines with optimization annealing to RNA inverse folding problem for identifying nucleotide sequences.
2/19/2026
Retrieval-Augmented Foundation Models for Matched Molecular Pair Transformations to Recapitulate Medicinal Chemistry Intuition
Applies retrieval-augmented foundation models to matched molecular pair transformations for drug discovery and medicinal chemistry analog generation.
2/19/2026
Protecting the Undeleted in Machine Unlearning
Demonstrates privacy risks in machine unlearning: reconstruction attacks show remaining data can be exposed when perfect retraining is pursued.
2/19/2026
Causality is Key for Interpretability Claims to Generalise
Argues causal inference is necessary for valid interpretability claims in LLMs, critiquing non-generalizable findings and unsupported causal interpretations.
2/19/2026
Knowledge-Embedded Latent Projection for Robust Representation Learning
Proposes latent space methods for analyzing high-dimensional discrete data in EHR applications with imbalanced matrix dimensions.
2/19/2026
Do Personality Traits Interfere? Geometric Limitations of Steering in Large Language Models
Studies geometric constraints on personality trait steering in LLMs (LLaMA, Mistral), examining whether Big Five traits can be independently controlled via steering vectors.
2/19/2026
Building Safe and Deployable Clinical Natural Language Processing under Temporal Leakage Constraints
Clinical NLP safety analysis addressing temporal leakage in discharge planning models and deployment risk mitigation.
2/19/2026
MARVL: Multi-Stage Guidance for Robotic Manipulation via Vision-Language Models
MARVL uses vision-language models for multi-stage reward design in robotic manipulation RL, addressing spatial grounding and task semantics.
2/19/2026
P-RAG: Prompt-Enhanced Parametric RAG with LoRA and Selective CoT for Biomedical and Multi-Hop QA
P-RAG combines parametric and retrieval-augmented generation with LoRA and selective chain-of-thought for biomedical QA.
2/19/2026
NeuroSleep: Neuromorphic Event-Driven Single-Channel EEG Sleep Staging for Edge-Efficient Sensing
Event-driven neuromorphic system for energy-efficient EEG-based sleep staging on edge devices.
2/19/2026
Surrogate Modeling for Neutron Transport: A Neural Operator Approach
Neural operator surrogates (DeepONet, FNO) for accelerating neutron transport computations in physics simulations.
2/19/2026
Learning to Drive in New Cities Without Human Demonstrations
Self-play multi-agent reinforcement learning for autonomous driving policy adaptation to new cities without human demonstrations.
2/19/2026
Quality-constrained Entropy Maximization Policy Optimization for LLM Diversity
Quality-constrained entropy maximization framework for LLM fine-tuning balancing output diversity and alignment quality.
2/19/2026
Steering Dynamical Regimes of Diffusion Models by Breaking Detailed Balance
Non-reversible diffusion process acceleration by breaking detailed balance in generative models while preserving stationary distribution.
2/19/2026
Generalized Leverage Score for Scalable Assessment of Privacy Vulnerability
Leverage score methodology for assessing privacy vulnerability and membership inference attack risk without model retraining.
2/19/2026
Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models
Graph learning approach for Gaussian graphical models incorporating node textual metadata via Laplacian constraints.
2/19/2026
World Action Models are Zero-shot Policies
DreamZero world action model using video diffusion for zero-shot robotic control by learning physical dynamics and generalizing to unseen environments.
2/19/2026
A fully differentiable framework for training proxy Exchange Correlation Functionals for periodic systems
Differentiable framework integrating ML models into density functional theory for exchange-correlation functionals in periodic systems.
2/19/2026
A Study on Real-time Object Detection using Deep Learning
Survey of real-time object detection using deep learning across applications like surveillance, AR/VR, and traffic monitoring.
2/19/2026
Visual Memory Injection Attacks for Multi-Turn Conversations
Security analysis of vision-language models in multi-turn conversations, exploring injection attacks via manipulated images.