3/11/2026
Causally Sufficient and Necessary Feature Expansion for Class-Incremental Learning
Causal feature expansion approach for class-incremental learning addressing catastrophic forgetting and feature collisions.
3/11/2026
Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL
Learning netlist representations from imperfect LLM-generated RTL code for hardware design without large labeled datasets.
3/11/2026
GIAT: A Geologically-Informed Attention Transformer for Lithology Identification
Transformer model with geological priors for lithology identification from well logs with improved interpretability.
3/11/2026
Better Bounds for the Distributed Experts Problem
Theoretical bounds for distributed expert selection problem across multiple servers minimizing regret.
3/11/2026
Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
Hybrid model combining discrete diffusion and autoregressive language models for improved multi-agent reasoning and planning.
3/11/2026
$P^2$GNN: Two Prototype Sets to boost GNN Performance
Graph neural network improvement using dual prototype sets to handle global context and noisy local neighborhoods.
3/11/2026
The Radio-Frequency Transformer for Signal Separation
Transformer-based signal separator for isolating signals from non-Gaussian interference using learned tokenization.
3/11/2026
Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
Game-theoretic approach to multi-agent RL using risk-sensitive equilibrium for robust and efficient agent coordination.
3/11/2026
Beyond Test-Time Training: Learning to Reason via Hardware-Efficient Optimal Control
Optimal control formulation for reasoning in language models to enable planning and goal-directed action selection.
3/11/2026
Efficient Reasoning at Fixed Test-Time Cost via Length-Aware Attention Priors and Gain-Aware Training
Methods for efficient reasoning in Transformers at fixed test-time cost using attention priors and training techniques.
3/11/2026
DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data
Spiking neural networks for spatiotemporal event-based data classification with improved energy efficiency and temporal decoding.
3/11/2026
Proxy-Guided Measurement Calibration
Method for calibrating measurement error in aggregate outcome variables from surveys and administrative records.
3/11/2026
A Gaussian Comparison Theorem for Training Dynamics in Machine Learning
Theoretical analysis connecting training dynamics in Gaussian mixture models to surrogate systems using Gordon comparison theorem.
3/11/2026
Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learning
Reward-Zero: implicit reward mechanism using language embeddings to derive progress signals for reinforcement learning without explicit reward functions.
3/11/2026
TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection
Graph neural network model for detecting anomalies across multiple domains with adaptive testing-time mechanisms to handle domain shift.
3/11/2026
Interactive 3D visualization of surface roughness predictions in additive manufacturing: A data-driven framework
Data-driven framework predicting surface roughness in 3D additive manufacturing using process parameters and surface geometry.
3/11/2026
Democratising Clinical AI through Dataset Condensation for Classical Clinical Models
Dataset condensation method for clinical ML models using synthetic data and differential privacy to democratize healthcare AI while protecting patient privacy.
3/11/2026
From Representation to Clusters: A Contrastive Learning Approach for Attributed Hypergraph Clustering
Contrastive learning approach for attributed hypergraph clustering with direct clustering supervision integration.
3/11/2026
SPAARS: Safer RL Policy Alignment through Abstract Exploration and Refined Exploitation of Action Space
SPAARS: offline-to-online RL safety method for robotics using abstract exploration and refined action space exploitation.
3/11/2026
Reconstructing Movement from Sparse Samples: Enhanced Spatio-Temporal Matching Strategies for Low-Frequency Data
Improvements to spatial-temporal matching algorithm for GPS trajectory to road network matching in sparse sampling scenarios.
3/11/2026
Impact of Markov Decision Process Design on Sim-to-Real Reinforcement Learning
Analysis of MDP design choices impact on sim-to-real transfer in reinforcement learning for industrial process control.
3/11/2026
From Weighting to Modeling: A Nonparametric Estimator for Off-Policy Evaluation
Nonparametric off-policy evaluation method for contextual bandits addressing limitations of inverse probability weighting.
3/11/2026
Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection
Temporal-conditioned normalizing flows framework for multivariate time series anomaly detection with uncertainty modeling.
3/11/2026
Compiler-First State Space Duality and Portable $O(1)$ Autoregressive Caching for Inference
XLA-compatible state space model inference implementation enabling O(1) autoregressive caching without NVIDIA hardware dependency.
3/11/2026
Learning Bayesian and Markov Networks with an Unreliable Oracle
Constraint-based structure learning for Markov and Bayesian networks with unreliable conditional independence oracles.
3/11/2026
An Optimal Control Approach To Transformer Training
Optimal control-theoretic framework for transformer training with structured constraints and McKean-Vlasov dynamics.
3/11/2026
Routing without Forgetting
Routing mechanism for online continual learning in transformers without forgetting, addressing non-stationary streaming data.
3/11/2026
Memorization capacity of deep ReLU neural networks characterized by width and depth
Theoretical analysis of memorization capacity in deep ReLU networks characterized by width and depth parameters.
3/11/2026
MM-algorithms for traditional and convex NMF with Tweedie and Negative Binomial cost functions and empirical evaluation
MM-algorithms for non-negative matrix factorization with Tweedie and Negative Binomial cost functions for unsupervised learning and feature extraction.
3/11/2026
Learning the Hierarchical Organization in Brain Network for Brain Disorder Diagnosis
Brain network analysis using hierarchical organization learning from fMRI data for brain disorder diagnosis.
3/11/2026
Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs
Conditional GAN framework for synthesizing subsurface rock formation images from sparse petrography data and well logs.
3/11/2026
FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting
FreqCycle framework for time series forecasting using multi-scale time-frequency analysis to capture mid to high frequency patterns.
3/11/2026
No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models
Research on how label and selection bias impact ML classification model evaluation, performance, and mitigation strategies.
3/11/2026
GNNs for Time Series Anomaly Detection: An Open-Source Framework and a Critical Evaluation
Open-source framework evaluating graph neural networks for time series anomaly detection with critical benchmarking.
3/11/2026
On Catastrophic Forgetting in Low-Rank Decomposition-Based Parameter-Efficient Fine-Tuning
Empirical study of catastrophic forgetting in LoRA and parameter-efficient fine-tuning methods during sequential learning.
3/11/2026
ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning
Active learning pipeline for efficiently generating preference data annotations for RLHF-based LLM alignment.
3/11/2026
Physics-informed neural operator for predictive parametric phase-field modelling
Physics-informed neural operators for accelerating parametric phase-field modeling in materials science.
3/11/2026
A Multi-Prototype-Guided Federated Knowledge Distillation Approach in AI-RAN Enabled Multi-Access Edge Computing System
Federated knowledge distillation approach for AI-native radio access networks in multi-access edge computing systems.
3/11/2026
Upper Generalization Bounds for Neural Oscillators
Theoretical generalization bounds for neural oscillators based on second-order ODEs for modeling dynamic systems.
3/11/2026
A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines
Hybrid quantum-classical framework using quantum circuit born machines for financial volatility forecasting.
3/11/2026
Exploiting Label-Aware Channel Scoring for Adaptive Channel Pruning in Split Learning
Adaptive channel pruning scheme for split learning to reduce communication overhead in distributed training.
3/11/2026
Information Theoretic Bayesian Optimization over the Probability Simplex
Bayesian optimization algorithm for optimizing probability distributions and mixtures on the probability simplex.
3/11/2026
Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning
In-context reinforcement learning approach that uses high-quality reasoning traces as better demonstrations for improving LLM reasoning.
3/11/2026
Correction of Transformer-Based Models with Smoothing Pseudo-Projector
Lightweight pseudo-projector modification for transformer-based language models to reduce noise sensitivity in hidden representations.
3/11/2026
A Unified Hierarchical Multi-Task Multi-Fidelity Framework for Data-Efficient Surrogate Modeling in Manufacturing
Multi-task multi-fidelity surrogate modeling framework for manufacturing systems using heterogeneous data sources.
3/11/2026
A Graph-Based Approach to Spectrum Demand Prediction Using Hierarchical Attention Networks
Graph attention network model for predicting spectrum demand using geospatial data in wireless networks.
3/11/2026
GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection
GAST combines gradient-aligned sparse tuning with data-layer selection for parameter-efficient fine-tuning of large language models.
3/11/2026
CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning
CarbonBench standardizes evaluation of zero-shot spatial transfer learning for upscaling carbon flux measurements across geographic regions.
3/11/2026
MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning
MSSR is a memory-aware replay strategy for continual LLM fine-tuning that reduces catastrophic forgetting during sequential task learning.
3/11/2026
OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality
OptEMA optimizer improves exponential moving average with adaptive stepsizes, achieving zero-noise optimality for stochastic optimization.