2/16/2026
AdaGrad-Diff: A New Version of the Adaptive Gradient Algorithm
AdaGrad variant using cumulative squared gradient differences instead of norms for adaptive stepsize learning.
2/16/2026
Realistic Face Reconstruction from Facial Embeddings via Diffusion Models
Reconstructing high-resolution face images from facial embeddings using diffusion models to test privacy risks in face recognition systems.
2/16/2026
Selection of CMIP6 Models for Regional Precipitation Projection and Climate Change Assessment in the Jhelum and Chenab River Basins
Climate model selection for precipitation projection in river basins using CMIP6 and machine learning techniques.
2/16/2026
Imitating What Works: Simulation-Filtered Modular Policy Learning from Human Videos
Learning robot manipulation skills from human videos using simulation filtering and modular policies for grasping and post-grasp motions.
2/16/2026
DART: aDaptive Accept RejecT for non-linear top-K subset identification
DART algorithm for non-linear top-K arm selection in combinatorial bandits with adaptive accept-reject sampling.
2/16/2026
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
Method leveraging low-rank structures and compressible parameter dynamics to reduce computational costs in overparameterized neural network learning.
2/16/2026
LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting
LTSM-Bundle: toolbox and benchmark for using large language models as universal time series forecasting models on heterogeneous datasets.
2/16/2026
Generating Physical Dynamics under Priors
Framework for incorporating physical priors into diffusion-based generative models to generate physically feasible dynamics.
2/16/2026
Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning
Analysis of the modality gap in contrastive multimodal learning (CLIP-like models) and methods to explain and reduce representation misalignment between modalities.
2/16/2026
B3C: A Minimalist Approach to Offline Multi-Agent Reinforcement Learning
B3C: minimalist offline multi-agent reinforcement learning approach using behavior cloning regularization to address overestimation in action selection.
2/16/2026
Memory Injection Attacks on LLM Agents via Query-Only Interaction
MINJA attack: adversarial method for injecting malicious data into LLM agent memory banks via query-only interactions without direct memory access.
2/16/2026
Data-Driven Worker Activity Recognition and Efficiency Estimation in Manual Fruit Harvesting
System for recognizing worker activities and estimating picker efficiency in commercial strawberry harvesting using instrumented equipment.
2/16/2026
Leveraging Noisy Manual Labels as Useful Information: An Information Fusion Approach for Enhanced Variable Selection in Penalized Logistic Regression
Method using noisy manual labels as information sources to enhance variable selection in penalized logistic regression.
2/16/2026
Learning on a Razor's Edge: Identifiability and Singularity of Polynomial Neural Networks
Theoretical analysis of identifiability and singularity in polynomial neural networks and their neuromanifolds.
2/16/2026
Optimal Formats for Weight Quantisation
Framework for systematic design and analysis of weight quantization formats for efficient deep learning model training and deployment.
2/16/2026
Beyond All-to-All: Causal-Aligned Transformer with Dynamic Structure Learning for Multivariate Time Series Forecasting
Transformer model with dynamic structure learning for multivariate time series forecasting using causal relationships instead of all-to-all connections.
2/16/2026
On Learning Verifiers and Implications to Chain-of-Thought Reasoning
Research on learning verifiers for chain-of-thought reasoning in LLMs using formal verification to improve mathematical problem-solving.
2/16/2026
N$^2$: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
N², a unified Python package for nearest neighbor-based matrix completion with theoretical guarantees and empirical benchmarks.
2/16/2026
Quasiparticle Interference Kernel Extraction with Variational Autoencoders via Latent Alignment
Variational autoencoder method for extracting quasiparticle interference patterns from quantum material imaging data.
2/16/2026
PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep Learning
PeakWeather dataset of Swiss weather station measurements for training spatiotemporal deep learning models for weather forecasting.
2/16/2026
Holistic Continual Learning under Concept Drift with Adaptive Memory Realignment
Framework for continual learning that handles concept drift in real-world data streams while preventing catastrophic forgetting.
2/16/2026
Adopting a human developmental visual diet yields robust, shape-based AI vision
Research on improving AI vision robustness by training on human developmental visual patterns to reduce reliance on texture and increase shape recognition.
2/16/2026
GAGA: Gaussianity-Aware Gaussian Approximation for Efficient 3D Molecular Generation
Efficient 3D molecular generation method using Gaussian probability paths with reduced sampling steps for drug discovery applications.
2/16/2026
FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation
Foundation model for analyzing industrial signals from SCADA systems across multiple modalities for anomaly detection.
2/16/2026
Instruction-based Time Series Editing
Instruction-based diffusion model for editing time series properties while preserving specified conditions, replacing rigid attribute vectors.
2/16/2026
Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
Federated learning approach using generative models to address data heterogeneity across distributed clients and improve model generalization.
2/16/2026
R-Zero: Self-Evolving Reasoning LLM from Zero Data
Self-evolving LLM that autonomously generates training data and improves reasoning without relying on human-curated tasks or labels.
2/16/2026
Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
Semantic caching system for reducing LLM inference costs by retrieving cached responses based on query similarity rather than exact matches.
2/16/2026
Self-Supervised Temporal Super-Resolution of Energy Data using Generative Adversarial Transformer
Generative adversarial transformer model for upsampling energy time series data with improved fidelity over conventional methods.
2/16/2026
MissionHD: Hyperdimensional Refinement of Distribution-Deficient Reasoning Graphs for Video Anomaly Detection
Hyperdimensional refinement method for LLM-generated reasoning graphs in video anomaly detection handling distribution-deficient structures.
2/16/2026
Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
Neural network architecture learning nonharmonic Fourier series with cosine activations for scientific machine learning tasks.
2/16/2026
Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
Fast approximate softmax attention mechanism clustering queries and keys for 36% faster transformer pretraining on long sequences.
2/16/2026
Online reinforcement learning via sparse Gaussian mixture model Q-functions
Online reinforcement learning framework using sparse Gaussian mixture model Q-functions with interpretable policy iteration.
2/16/2026
Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization
Diffusion-based scenario tree generation for stochastic forecasting and multistage optimization in energy and finance domains.
2/16/2026
Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
Adaptive time series foundation model with parameter-efficient design handling temporal heterogeneity and varying sampling rates.
2/16/2026
Multi-Agent Stage-wise Conservative Linear Bandits
Multi-agent linear bandit algorithm with stage-wise safety constraints for collaborative learning in networked settings.
2/16/2026
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
Vector diffusion wavelets integrated into geometric graph neural networks for point cloud and manifold data representation.
2/16/2026
What Do Temporal Graph Learning Models Learn?
Investigation into what temporal graph learning models actually learn despite benchmark claims, revealing evaluation protocol issues.
2/16/2026
Provable Training Data Identification for Large Language Models
Statistical set-level inference framework to identify training data in large language models with controlled error rates for legal evidence.
2/16/2026
Don't Walk the Line: Boundary Guidance for Filtered Generation
Reinforcement learning method to fine-tune generative models avoiding decision boundary mode-seeking when paired with safety classifiers.
2/16/2026
Multi-Window Temporal Analysis for Enhanced Arrhythmia Classification: Leveraging Long-Range Dependencies in Electrocardiogram Signals
Deep learning method analyzing extended ECG windows to improve arrhythmia classification specificity and cross-dataset generalization.
2/16/2026
Weight Decay may matter more than muP for Learning Rate Transfer in Practice
Weight decay regularization has greater impact than maximal update parameterization for transferring learning rates across model scales.
2/16/2026
Active Learning with Task-Driven Representations for Messy Pools
Active learning approach using task-driven representations to select relevant samples from uncurated, messy data pools.
2/16/2026
LLMs as In-Context Meta-Learners for Model and Hyperparameter Selection
Large language models used as in-context meta-learners to recommend model families and hyperparameters from dataset metadata.
2/16/2026
Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-off
Federated learning framework over wireless networks handling heterogeneous device conditions through bias-variance optimization.
2/16/2026
Context-Specific Causal Graph Discovery with Unobserved Contexts: Non-Stationarity, Regimes and Spatio-Temporal Patterns
Causal graph discovery method for spatially gridded time series data with non-stationary regimes and varying patterns.
2/16/2026
Quantum Temporal Convolutional Neural Networks for Cross-Sectional Equity Return Prediction: A Comparative Benchmark Study
Quantum temporal convolutional neural network applied to stock market prediction with classical temporal encoder component.
2/16/2026
Membership and Dataset Inference Attacks on Large Audio Generative Models
Methods to detect if specific audio data was used in training generative audio models through membership and dataset inference attacks.
2/16/2026
ATLAS: Adaptive Topology-based Learning at Scale for Homophilic and Heterophilic Graphs
Graph neural network framework for handling heterophilic graphs without iterative message passing using multi-resolution community features.
2/16/2026
Imitation Learning for Combinatorial Optimisation under Uncertainty
Imitation learning framework for combinatorial optimization under uncertainty. Explores role of expert demonstrations in training policies for sequential decision problems.