2/25/2026
Diffusion Modulation via Environment Mechanism Modeling for Planning
Diffusion-based planning method for offline reinforcement learning with environment mechanism modeling to ensure trajectory consistency.
2/25/2026
Heterogeneity-Aware Client Selection Methodology For Efficient Federated Learning
Heterogeneity-aware client selection for federated learning to improve model accuracy across statistical heterogeneous clients.
2/25/2026
Prior-Agnostic Incentive-Compatible Exploration
Prior-agnostic incentive-compatible exploration in bandit settings with multiple sequential agents.
2/25/2026
PhyGHT: Physics-Guided HyperGraph Transformer for Signal Purification at the HL-LHC
Physics-guided HyperGraph Transformer for signal extraction from particle collision data at CERN's HL-LHC.
2/25/2026
ActionEngine: From Reactive to Programmatic GUI Agents via State Machine Memory
ActionEngine: training-free framework for GUI agents using state machine memory to reduce costs, latency, and improve accuracy vs reactive vision-language model approaches.
2/25/2026
Inner Speech as Behavior Guides: Steerable Imitation of Diverse Behaviors for Human-AI coordination
Inner speech guides steerable imitation learning for human-AI coordination, capturing behavioral diversity and non-Markovian human behaviors.
2/25/2026
Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
STAR-LDM integrates latent diffusion planning with autoregressive generation, enabling semantic planning before token commitment.
2/25/2026
Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with $C^{s,\lambda}$ Targets
Theoretical proof that standard Transformers achieve minimax approximation rate for Hölder functions in nonparametric regression.
2/25/2026
Personal Information Parroting in Language Models
Personal information memorization in language models: detector suite for email, phone, IP addresses outperforms existing regex baselines.
2/25/2026
Characterizing Online and Private Learnability under Distributional Constraints via Generalized Smoothness
Learning theory characterizing online and private learnability under distributional constraints via generalized smoothness.
2/25/2026
Amortized Bayesian inference for actigraph time sheet data from mobile devices
Bayesian inference methods for analyzing high-resolution actigraph wearable device health and mobility data.
2/25/2026
Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Interpretable open-world object detection framework using concept decomposition to distinguish known from unknown objects.
2/25/2026
On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
Theoretical analysis of SGD convergence with perturbations in forward-backward passes through sequential operators.
2/25/2026
DANCE: Doubly Adaptive Neighborhood Conformal Estimation
DANCE method for conformal prediction uncertainty quantification using adaptive neighborhood estimation with pre-trained deep learning models.
2/25/2026
Vision-Language Models for Ergonomic Assessment of Manual Lifting Tasks: Estimating Horizontal and Vertical Hand Distances from RGB Video
Vision-language models applied to ergonomic assessment by estimating hand distances from RGB video for NIOSH lifting equation.
2/25/2026
F10.7 Index Prediction: A Multiscale Decomposition Strategy with Wavelet Transform for Performance Optimization
F10.7 solar index forecasting using wavelet decomposition and iTransformer model with sunspot number features.
2/25/2026
Communication-Inspired Tokenization for Structured Image Representations
Communication-inspired discrete image tokenizer for vision transformers optimized for semantic structure over texture reconstruction.
2/25/2026
SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing
SibylSense enables adaptive reward rubric learning for open-ended generation via memory tuning and adversarial probing to prevent reward hacking.
2/25/2026
Assessing the Impact of Speaker Identity in Speech Spoofing Detection
Speech spoofing detection system analysis examining impact of speaker identity on detection embeddings and robustness.
2/25/2026
Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation
Tail-aware divergence for language model distillation that decouples top-K probabilities to improve knowledge transfer from teacher to student models.
2/25/2026
DRESS: A Continuous Framework for Structural Graph Refinement
DRESS framework addresses computational complexity of higher-order Weisfeiler-Lehman graph analysis using continuous dynamical systems.
2/25/2026
Functional Continuous Decomposition
Functional Continuous Decomposition framework for non-stationary time-series analysis with parametric optimization and guaranteed continuity.
2/25/2026
SpatiaLQA: A Benchmark for Evaluating Spatial Logical Reasoning in Vision-Language Models
SpatiaLQA benchmark evaluates spatial logical reasoning capabilities in vision-language models for real-world scenarios.
2/25/2026
Some Simple Economics of AGI
Economic analysis of AGI impact on labor, marginal costs, and human verification as binding constraint on growth.
2/25/2026
Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures
MRI brain lesion segmentation using report-supervised learning with multi-parametric scans and substructures.
2/25/2026
MIP Candy: A Modular PyTorch Framework for Medical Image Processing
PyTorch framework for medical image processing with support for volumetric data and domain-specific training procedures.
2/25/2026
Empirically Calibrated Conditional Independence Tests
Empirical analysis of conditional independence tests for causal discovery, addressing failures in small samples and FDR control.
2/25/2026
Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise
Studies multi-distribution learning complexity with bounded label noise to determine if single-task 1/ε rates extend to multi-source settings.
2/25/2026
Position-Aware Sequential Attention for Accurate Next Item Recommendations
Improves sequential attention for recommendation systems by integrating position information into attention mechanism beyond additive embeddings.
2/25/2026
Motivation is Something You Need
Proposes dual-model training framework inspired by neuroscience motivation states with alternating base and larger model activation.
2/25/2026
An Enhanced Projection Pursuit Tree Classifier with Visual Methods for Assessing Algorithmic Improvements
Extends projection pursuit tree classifier with visual diagnostic methods for high-dimensional multi-class classification problems.
2/25/2026
Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
Analyzes complexity of classical acceleration (FISTA) for computing ℓ1-regularized PageRank with degree-weighted work bounds.
2/25/2026
LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Applies vision-language models to radiology imaging for decision support with longitudinal multi-modal chest X-ray analysis.
2/25/2026
A Benchmark for Deep Information Synthesis
DEEPSYNTH benchmark evaluates LLM-based agents on complex multi-source information synthesis tasks beyond fact retrieval.
2/25/2026
Scaling State-Space Models on Multiple GPUs with Tensor Parallelism
Implements tensor parallelism for selective state-space models on multi-GPU systems to scale SSM inference beyond single GPU limits.
2/25/2026
Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions
Decomposes epistemic uncertainty in Bayesian deep learning into per-class contributions for safety-critical classification asymmetric costs.
2/25/2026
Aletheia tackles FirstProof autonomously
Aletheia, a mathematics research AI agent powered by Gemini 3 Deep Think, autonomously solves 6 of 10 FirstProof challenge problems.
2/25/2026
Squint: Fast Visual Reinforcement Learning for Sim-to-Real Robotics
Combines off-policy and on-policy reinforcement learning for fast visual sim-to-real robotics training with minimal sample waste.
2/25/2026
Towards Attributions of Input Variables in a Coalition
Proposes coalition-based partitioning approach for Shapley value attribution methods in explainable AI to resolve attribution conflicts.
2/25/2026
Rethinking Disentanglement under Dependent Factors of Variation
Theoretical framework for disentangled representation learning when factors of variation are dependent rather than independent.
2/25/2026
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
Proposes dynamic optimal transport minimization for discrete flow matching on categorical data with Kantorovich formulation.
2/25/2026
Predicting Subway Passenger Flows under Incident Situation with Causality
Machine learning method for predicting subway passenger flows during incidents using causality-based two-stage approach.
2/25/2026
Characterizing LLM Inference Energy-Performance Tradeoffs across Workloads and GPU Scaling
Measurement-driven analysis of LLM inference energy and performance tradeoffs across workloads using GPU DVFS on 1B-32B parameter models.
2/25/2026
Universality of Benign Overfitting in Binary Linear Classification
Theoretical investigation of benign overfitting phenomenon in binary linear classification across over-parametrized neural networks.
2/25/2026
Safe Reinforcement Learning for Real-World Engine Control
Applies Deep Deterministic Policy Gradient (DDPG) reinforcement learning to engine control in a safety-critical testbench environment.
2/25/2026
A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers
Theoretical analysis of neural network-based optimal transport solvers using semi-dual adversarial formulations for generative modeling.
2/25/2026
Improving the Convergence of Private Shuffled Gradient Methods with Public Data
Theoretical analysis of differentially private shuffled gradient methods for convex ERM, addressing privacy-accuracy tradeoffs compared to standard DP-SGD.
2/25/2026
Using the Path of Least Resistance to Explain Deep Networks
Analyzes flaws in Integrated Gradients attribution method and proposes alternative path-based approach using model-induced geometry for better feature importance explanations.
2/25/2026
Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence
Proposes Cauchy-Schwarz divergence for vision-language alignment to address distributional differences and alignment-uniformity conflicts in multimodal models.
2/25/2026
Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
Semantic Parallelism optimizes MoE LLM inference by co-scheduling model device placement and request routing, reducing communication overhead in multi-device serving.