2/25/2026
High-Dimensional Robust Mean Estimation with Untrusted Batches
Addresses high-dimensional mean estimation in collaborative learning with statistically heterogeneous and adversarial data sources.
2/25/2026
WeirNet: A Large-Scale 3D CFD Benchmark for Geometric Surrogate Modeling of Piano Key Weirs
Large-scale 3D CFD benchmark dataset (WeirNet) for surrogate modeling of piano key weir hydraulic performance.
2/25/2026
Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
Introduces Fuz-RL, a fuzzy-guided framework for safe reinforcement learning under multiple uncertainty sources with interpretable risk assessment.
2/25/2026
Rethink Efficiency Side of Neural Combinatorial Solver: An Offline and Self-Play Paradigm
Proposes ECO, an offline self-play learning paradigm using Direct Preference Optimization and Mamba architecture for neural combinatorial optimization.
2/25/2026
On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
Applies federated learning to electric vehicle energy demand forecasting for smart grid optimization.
2/25/2026
Understanding the Role of Rehearsal Scale in Continual Learning under Varying Model Capacities
Studies how rehearsal scale affects learning dynamics in continual learning algorithms across varying model capacities.
2/25/2026
Exploring the Impact of Parameter Update Magnitude on Forgetting and Generalization of Continual Learning
Characterizes catastrophic forgetting in continual learning through parameter update magnitude, formalizing knowledge degradation from task-specific drift.
2/25/2026
Probing Dec-POMDP Reasoning in Cooperative MARL
Analyzes reasoning capabilities in cooperative multi-agent reinforcement learning under Dec-POMDP framework with partial observability and decentralized coordination.
2/25/2026
Regret-Guided Search Control for Efficient Learning in AlphaZero
Proposes regret-guided search control for AlphaZero to improve learning efficiency through targeted state revisitation in reinforcement learning.
2/25/2026
Transcoder Adapters for Reasoning-Model Diffing
Introduces transcoder adapters to interpret MLP computation differences in reasoning models, comparing Qwen2.5-Math-7B and DeepSeek-R1-Distilled variants.
2/25/2026
From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning
Semantic-guided expert forest method for class-incremental learning that organizes adapter knowledge through task relationships.
2/25/2026
Hierarchic-EEG2Text: Assessing EEG-To-Text Decoding across Hierarchical Abstraction Levels
EEG-to-text decoding system assessing hierarchical abstraction levels for fine-grained brain signal interpretation across multiple classes.
2/25/2026
Extending $\mu$P: Spectral Conditions for Feature Learning Across Optimizers
Extension of maximal update parameterization for hyperparameter transfer across different optimizers in large language model training.
2/25/2026
Estimation of Confidence Bounds in Binary Classification using Wilson Score Kernel Density Estimation
Method for estimating confidence bounds in binary classifiers using Wilson Score kernel density estimation for critical applications.
2/25/2026
Does Order Matter : Connecting The Law of Robustness to Robust Generalization
Theoretical work connecting law of robustness to robust generalization in neural networks through Lipschitz constraints.
2/25/2026
MAST: A Multi-fidelity Augmented Surrogate model via Spatial Trust-weighting
Multi-fidelity surrogate modeling technique combining low and high-fidelity simulation data with spatial trust-weighting.
2/25/2026
Matching Multiple Experts: On the Exploitability of Multi-Agent Imitation Learning
Theoretical analysis of multi-agent imitation learning showing impossibility and hardness results for learning low-exploitable policies offline.
2/25/2026
T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Neural network architecture for multivariate time series imputation using channel-head binding to transfer information across variables.
2/25/2026
PIME: Prototype-based Interpretable MCTS-Enhanced Brain Network Analysis for Disorder Diagnosis
Interpretable framework for fMRI-based brain disorder diagnosis combining prototype learning with Monte Carlo tree search.
2/25/2026
Localized Dynamics-Aware Domain Adaption for Off-Dynamics Offline Reinforcement Learning
Domain adaptation method for offline reinforcement learning addressing dynamics mismatch through localized similarity matching.
2/25/2026
ProxyFL: A Proxy-Guided Framework for Federated Semi-Supervised Learning
Federated semi-supervised learning framework using proxy guidance to handle data heterogeneity across and within distributed clients.
2/25/2026
Scaling Vision Transformers: Evaluating DeepSpeed for Image-Centric Workloads
Evaluation of DeepSpeed distributed training framework for scaling Vision Transformer models to address computational and memory demands.
2/25/2026
Probing Graph Neural Network Activation Patterns Through Graph Topology
Analysis of Graph Neural Network activation patterns through graph topology and curvature to understand oversmoothing and oversquashing artifacts.
2/25/2026
SOM-VQ: Topology-Aware Tokenization for Interactive Generative Models
Tokenization method combining vector quantization with Self-Organizing Maps to create structured discrete codebooks for interactive generative models.
2/25/2026
SELAUR: Self Evolving LLM Agent via Uncertainty-aware Rewards
Self-evolving LLM agent framework using uncertainty-aware rewards to guide multi-step decision-making and improve learning signal for agent training.
2/25/2026
Sequential Counterfactual Inference for Temporal Clinical Data: Addressing the Time Traveler Dilemma
Framework for counterfactual inference on temporal clinical data distinguishing immutable from controllable features in electronic health records.
2/25/2026
The Diffusion Duality, Chapter II: $\Psi$-Samplers and Efficient Curriculum
Study on Predictor-Corrector samplers for discrete diffusion models to improve multi-step generation quality beyond ancestral sampling methods.
2/25/2026
Why Pass@k Optimization Can Degrade Pass@1: Prompt Interference in LLM Post-training
Research on Pass@k metric optimization for LLMs showing trade-offs between multi-sample and single-sample inference performance in code generation and reasoning tasks.
2/25/2026
Statistical Query Lower Bounds for Smoothed Agnostic Learning
Statistical query lower bounds for learning halfspaces under Gaussian perturbations in the smoothed agnostic learning model.
2/25/2026
Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
Untied Ulysses: memory-efficient context parallelism technique for long sequences via headwise chunking in Transformers.
2/25/2026
Learning from Trials and Errors: Reflective Test-Time Planning for Embodied LLMs
Reflective Test-Time Planning for embodied LLMs combining in-action and post-action reflection with test-time scaling for robot task learning.
2/25/2026
Test-Time Training with KV Binding Is Secretly Linear Attention
Analysis revealing that test-time training with KV binding can be expressed as learned linear attention mechanism.
2/25/2026
SMaRT: Online Reusable Resource Assignment and an Application to Mediation in the Kenyan Judiciary
Online resource allocation algorithm for assigning mediators to judicial cases with quality learning.
2/25/2026
Benchmarking Distilled Language Models: Performance and Efficiency in Resource-Constrained Settings
Benchmark comparing knowledge-distilled small language models against vanilla and proprietary models for resource-constrained environments.
2/25/2026
VISION-ICE: Video-based Interpretation and Spatial Identification of Arrhythmia Origins via Neural Networks in Intracardiac Echocardiography
AI framework using neural networks on intracardiac echocardiography video to localize cardiac arrhythmia origins.
2/25/2026
Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Under Constrained Sensing
Leakage-aware benchmarking framework for early patient deterioration prediction under realistic emergency triage sensing constraints.
2/25/2026
Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Machine learning approach using axial vectors in equivariant networks for designing D-peptide binders targeting L-proteins.
2/25/2026
Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation
Physics-informed neural networks for estimating coolant velocity in MOSFET heat sinks given thermal conditions.
2/25/2026
Data-Driven Deep MIMO Detection:Network Architectures and Generalization Analysis
Deep learning approach for MIMO symbol detection using soft interference cancellation to reduce computational complexity.
2/25/2026
OrgFlow: Generative Modeling of Organic Crystal Structures from Molecular Graphs
Flow-matching generative model for predicting organic crystal structures from molecular graphs, addressing gaps in materials science.
2/25/2026
KEMP-PIP: A Feature-Fusion Based Approach for Pro-inflammatory Peptide Prediction
KEMP-PIP: hybrid machine learning framework combining protein language models with handcrafted features for pro-inflammatory peptide prediction.
2/25/2026
Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
Deep learning model for de novo peptide sequencing with explicit mass consistency constraints using regressor-guided diffusion.
2/25/2026
The Sim-to-Real Gap in MRS Quantification: A Systematic Deep Learning Validation for GABA
Deep learning validation for quantifying GABA metabolites from magnetic resonance spectroscopy signals.
2/25/2026
Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Theoretical analysis of gap-dependent regret bounds for reinforcement learning algorithms with linear function approximation.
2/25/2026
Multilevel Determinants of Overweight and Obesity Among U.S. Children Aged 10-17: Comparative Evaluation of Statistical and Machine Learning Approaches Using the 2021 National Survey of Children's Health
Comparison of statistical and machine learning approaches for predicting childhood obesity using survey data.
2/25/2026
An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
LLM-based framework for rare disease phenotyping from clinical notes, extracting and standardizing features to Human Phenotype Ontology terms.
2/25/2026
Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Thinking
Circuit tracing framework for vision-language models using transcoders and attribution graphs to analyze multimodal reasoning mechanisms.
2/25/2026
No One Size Fits All: QueryBandits for Hallucination Mitigation
QueryBandits: model-agnostic contextual bandit framework to mitigate hallucinations in closed-source LLMs through post-hoc detection and mitigation.
2/25/2026
Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Research: Zero-overhead online continual learning framework for deep neural network OFDM receivers adapting to time-varying communication channels.
2/25/2026
Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
Research on detecting and mitigating group bias in heterogeneous treatment effect predictions when aggregating ML model outputs to subgroups.