2/17/2026
Anonymization-Enhanced Privacy Protection for Mobile GUI Agents: Available but Invisible
Privacy protection method for mobile GUI agents using anonymization to mitigate exposure of sensitive data during screen processing.
2/17/2026
C^2ROPE: Causal Continuous Rotary Positional Encoding for 3D Large Multimodal-Models Reasoning
Causal continuous rotary positional encoding improving 3D feature alignment in multimodal LLMs for spatial reasoning tasks.
2/17/2026
LAP: Language-Action Pre-Training Enables Zero-shot Cross-Embodiment Transfer
Language-Action pre-training framework enabling zero-shot transfer of robot policies across different embodiments without fine-tuning.
2/17/2026
In-the-Wild Model Organisms: Mitigating Undesirable Emergent Behaviors in Production LLM Post-Training via Data Attribution
Data attribution method to trace and mitigate undesirable emergent behaviors in LLM post-training by identifying responsible datapoints.
2/17/2026
The Manifold of the Absolute: Religious Perennialism as Generative Inference
Applies variational autoencoder mathematics to formalize religious epistemology and perennialism.
2/17/2026
ReaDy-Go: Real-to-Sim Dynamic 3D Gaussian Splatting Simulation for Environment-Specific Visual Navigation with Moving Obstacles
3D Gaussian Splatting simulation framework for training visual navigation policies in dynamic environments with moving obstacles.
2/17/2026
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception
Method to improve fine-grained visual perception in multimodal LLMs by distilling zoomed regions without repeated inference calls.
2/17/2026
ExtractBench: A Benchmark and Evaluation Methodology for Complex Structured Extraction
Benchmark and methodology for evaluating LLM-based PDF-to-JSON extraction at enterprise scale with complex schema requirements.
2/17/2026
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Theoretical analysis of Jacobian spectra in deep neural networks to explain implicit bias in gradient-based training.
2/17/2026
Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward
Formalizes agent skills as composable packages enabling LLMs to extend capabilities dynamically without retraining, covering architecture, acquisition, and security.
2/17/2026
MedXIAOHE: A Comprehensive Recipe for Building Medical MLLMs
MedXIAOHE medical vision-language foundation model with entity-aware continual pretraining achieving state-of-the-art on medical benchmarks.
2/17/2026
Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery
Prior-guided symbolic regression framework incorporating scientific constraints to discover interpretable equations consistent with physical principles.
2/17/2026
Directional Concentration Uncertainty: A representational approach to uncertainty quantification for generative models
Directional Concentration Uncertainty framework for flexible uncertainty quantification in generative models across tasks and modalities.
2/17/2026
BLUEPRINT Rebuilding a Legacy: Multimodal Retrieval for Complex Engineering Drawings and Documents
Blueprint system for multimodal retrieval in engineering archives using layout-aware VLM OCR and identifier normalization.
2/17/2026
Exploring the Performance of ML/DL Architectures on the MNIST-1D Dataset
Comparative study of ML/DL architectures on MNIST-1D dataset for distinguishing neural network performance on controlled benchmarks.
2/17/2026
The Speed-up Factor: A Quantitative Multi-Iteration Active Learning Performance Metric
Review and proposed metrics for evaluating multi-iteration active learning query methods and sample selection strategies.
2/17/2026
Accelerated Discovery of Cryoprotectant Cocktails via Multi-Objective Bayesian Optimization
Multi-objective Bayesian optimization framework for designing cryoprotectant cocktails balancing ice suppression and cell toxicity.
2/17/2026
High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator
Diffusion-based downscaling of climate emulator for high-resolution weather projections addressing training instability and computational costs.
2/17/2026
Comparing Classifiers: A Case Study Using PyCM
Tutorial on PyCM library for comprehensive multi-class classifier evaluation and performance metrics comparison.
2/17/2026
Finding Highly Interpretable Prompt-Specific Circuits in Language Models
Research showing language model circuits are prompt-specific within tasks, not uniform across prompts, using causal communication analysis.
2/17/2026
Federated Learning of Nonlinear Temporal Dynamics with Graph Attention-based Cross-Client Interpretability
Federated learning framework for nonlinear temporal dynamics using graph attention for interpretable cross-client relationships without sharing raw data.
2/17/2026
Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity
Research identifies rank collapse phenomenon in federated low-rank adaptation with heterogeneous clients, proposing mitigation for privacy-preserving fine-tuning.
2/17/2026
TrasMuon: Trust-Region Adaptive Scaling for Orthogonalized Momentum Optimizers
TrasMuon optimizer enhances Muon-style methods with trust-region adaptive scaling to address training sensitivity and high-energy bursts.
2/17/2026
$\gamma$-weakly $\theta$-up-concavity: Linearizable Non-Convex Optimization with Applications to DR-Submodular and OSS Functions
Novel optimization framework for monotone non-convex functions unifying DR-submodular and OSS functions with theoretical convergence analysis.
2/17/2026
Singular Vectors of Attention Heads Align with Features
Study demonstrating singular vectors of attention heads align with learned features in language models, providing mechanistic interpretability foundations.
2/17/2026
QuaRK: A Quantum Reservoir Kernel for Time Series Learning
QuaRK framework combines quantum reservoir computing with classical readout for time series learning with theoretical guarantees.
2/17/2026
Fast Swap-Based Element Selection for Multiplication-Free Dimension Reduction
Fast algorithm for multiplication-free dimension reduction via element selection as alternative to PCA for reducing model parameters and accelerating inference.
2/17/2026
Out-of-Support Generalisation via Weight Space Sequence Modelling
Research on out-of-support generalization reformulates extrapolation beyond training data distribution as sequence modeling in weight space to prevent catastrophic failure.
2/17/2026
Scenario-Adaptive MU-MIMO OFDM Semantic Communication With Asymmetric Neural Network
Neural network approach for semantic communication in MU-MIMO OFDM systems handling multi-user interference and frequency-selective fading.
2/17/2026
Interpretable clustering via optimal multiway-split decision trees
Optimal multiway-split decision trees for interpretable clustering that balance accuracy and explainability while reducing computational costs.
2/17/2026
Benchmark Leakage Trap: Can We Trust LLM-based Recommendation?
Investigates benchmark data leakage in LLM-based recommender systems where models memorize training data, inflating evaluation metrics.
2/17/2026
Optimization-Free Graph Embedding via Distributional Kernel for Community Detection
Graph embedding method using distributional kernels for community detection without optimization, addressing over-smoothing in GNNs.
2/17/2026
Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series
Detects unusual evolving trends in time series using concept of time series chains capturing ordered temporal pattern changes.
2/17/2026
Cumulative Utility Parity for Fair Federated Learning under Intermittent Client Participation
Fairness approach for federated learning addressing cumulative utility parity under intermittent and heterogeneous client participation.
2/17/2026
Zero-Order Optimization for LLM Fine-Tuning via Learnable Direction Sampling
Zero-order optimization method for LLM fine-tuning via learnable direction sampling, reducing memory requirements without backpropagation.
2/17/2026
Optimized Certainty Equivalent Risk-Controlling Prediction Sets
Optimized certainty equivalent risk-controlling prediction sets for safety-critical applications with tail behavior and worst-case guarantees.
2/17/2026
ALMo: Interactive Aim-Limit-Defined, Multi-Objective System for Personalized High-Dose-Rate Brachytherapy Treatment Planning and Visualization for Cervical Cancer
Interactive multi-objective system for treatment planning in cervical cancer brachytherapy using ML-assisted clinical decision-making.
2/17/2026
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
Vision-language model calibration approach for class-incremental learning that addresses representation rigidity and accumulated errors in analytic CIL.
2/17/2026
On the Sparsifiability of Correlation Clustering: Approximation Guarantees under Edge Sampling
Studies sparsification-approximation tradeoffs for correlation clustering, analyzing how much edge information is needed for LP-based guarantees.
2/17/2026
Physics Aware Neural Networks: Denoising for Magnetic Navigation
Physics-informed neural networks for denoising magnetic field data in airborne navigation systems when GPS is unavailable.
2/17/2026
Attention Head Entropy of LLMs Predicts Answer Correctness
Uses attention head entropy to predict answer correctness in LLMs, enabling detection of hallucinations without external evaluators.
2/17/2026
Optimal Regret for Policy Optimization in Contextual Bandits
First optimal regret bound for policy optimization in contextual multi-armed bandits with general offline function approximation.
2/17/2026
Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
OPO-CMDP presents first policy optimization algorithm for contextual MDPs with general offline function approximation achieving near-optimal regret bounds.
2/17/2026
HBVLA: Pushing 1-Bit Post-Training Quantization for Vision-Language-Action Models
HBVLA applies 1-bit post-training quantization to vision-language-action models for efficient deployment on resource-constrained robots and edge devices.
2/17/2026
Data-driven Bi-level Optimization of Thermal Power Systems with embedded Artificial Neural Networks
Bi-level optimization framework using neural networks for operational optimization of thermal power systems with hierarchical variables.
2/17/2026
Discrete Double-Bracket Flows for Isotropic-Noise Invariant Eigendecomposition
Novel matrix-free eigendecomposition method using discrete double-bracket flows that is invariant to isotropic noise shifts.
2/17/2026
On Representation Redundancy in Large-Scale Instruction Tuning Data Selection
Study of instruction-tuning data selection for LLMs using semantic representation similarity to identify redundancy in large-scale datasets.
2/17/2026
MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models
MEMTS introduces parameterized memory for domain adaptation of time series foundation models to handle temporal distribution shifts and domain-specific patterns.
2/17/2026
MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction
MechPert predicts transcriptional responses to unseen genetic perturbations using mechanistic consensus as inductive bias, combining knowledge graphs with LLM reasoning.
2/17/2026
Cast-R1: Learning Tool-Augmented Sequential Decision Policies for Time Series Forecasting
Cast-R1 applies tool-augmented sequential decision policies and iterative reasoning to time series forecasting, enabling autonomous evidence acquisition and prediction revision.