3/25/2026
A Learning Method with Gap-Aware Generation for Heterogeneous DAG Scheduling
End-to-end reinforcement learning framework for heterogeneous DAG scheduling with gap-aware generation enabling rapid schedule adaptation across environments.
3/25/2026
Permutation-Symmetrized Diffusion for Unconditional Molecular Generation
Diffusion model for unconditional molecular generation using permutation symmetry on quotient manifolds to enforce invariance in point-cloud generation.
3/25/2026
SafeSeek: Universal Attribution of Safety Circuits in Language Models
Mechanistic interpretability framework identifying and attributing safety circuits in LLMs responsible for alignment, jailbreak, and backdoor behaviors.
3/25/2026
A Comparative Study of Machine Learning Models for Hourly Forecasting of Air Temperature and Relative Humidity
Comparative study of seven ML models (XGBoost, LSTM, CNN-LSTM, etc.) for hourly air temperature and humidity forecasting in Chongqing.
3/25/2026
Off-Policy Value-Based Reinforcement Learning for Large Language Models
Off-policy value-based reinforcement learning framework for LLMs enabling improved data utilization and sample efficiency for long-horizon tasks.
3/25/2026
Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation
Energy-based model for graph generation using transport-aligned sampling to improve efficiency and quality in discrete domain generation.
3/25/2026
SortedRL: Accelerating RL Training for LLMs through Online Length-Aware Scheduling
Length-aware scheduling method accelerating reinforcement learning training for LLMs by optimizing rollout phase efficiency during chain-of-thought generation.
3/25/2026
Similarity-Aware Mixture-of-Experts for Data-Efficient Continual Learning
Continual learning framework using mixture-of-experts with similarity awareness for data-efficient adaptation to new tasks with limited samples.
3/25/2026
End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions
Computationally efficient reinforcement learning algorithm for linear function approximation in MDPs satisfying linear Bellman completeness.
3/25/2026
Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
Federated learning approach combining differential privacy and Byzantine robustness to protect against both data leakage and adversarial server attacks.
3/25/2026
Estimating Flow Velocity and Vehicle Angle-of-Attack from Non-invasive Piezoelectric Structural Measurements Using Deep Learning
Deep learning method for estimating aerodynamic variables (velocity, angle-of-attack) from piezoelectric sensor measurements on aircraft structures.
3/25/2026
Evaluating Prompting Strategies for Chart Question Answering with Large Language Models
Systematic evaluation of prompting strategies (zero-shot, few-shot, chain-of-thought) for chart question answering across GPT-3.5, GPT-4, and GPT-4o models on ChartQA dataset.
3/25/2026
TIPS: Turn-Level Information-Potential Reward Shaping for Search-Augmented LLMs
TIPS framework improves RL training for search-augmented LLMs via turn-level reward shaping, addressing sparse rewards and credit assignment in reasoning tasks.
3/25/2026
The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis
Multi-agent reinforcement learning agents develop efficient private communication protocol; performance drops with human-comprehensible language enforced.
3/25/2026
Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-structure prediction
CHANRG benchmark reveals limited generalization of RNA secondary-structure prediction models. 170K structured RNA families dataset.
3/25/2026
Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study
Quantitative assessment of reference retrieval errors from 5 LLM platforms on 2,000 medical literature references. Evaluates Grok-2, ChatGPT, Gemini, Perplexity, DeepSeek.
3/25/2026
Intelligence Inertia: Physical Principles and Applications
Theoretical paper on thermodynamic principles and computational costs of maintaining symbolic interpretability in AI systems.
3/25/2026
Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
Theoretical analysis of low-rank knowledge distillation for LLMs with convergence and generalization guarantees. Covers compression techniques for efficient deployment.
3/25/2026
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection
Quantum-enhanced graph neural network for network intrusion detection exploiting relational dependencies in network traffic.
3/25/2026
Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks
Quantum federated autoencoder for anomaly detection in IoT networks using distributed learning without centralizing raw data.
3/25/2026
SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts
Multimodal fusion framework for predicting synthetic lethality in cancer drug development. Domain-specific bioinformatics research.
3/25/2026
Latent Style-based Quantum Wasserstein GAN for Drug Design
Quantum Wasserstein GAN for de novo drug design using generative AI. Focuses on drug discovery rather than ML applications or tools.
3/25/2026
Probabilistic modeling over permutations using quantum computers
Quantum computing approach for probabilistic modeling over permutation-structured data using super-exponential symmetric group Fourier transform speedup.
3/25/2026
Computational Arbitrage in AI Model Markets
Framework for computational arbitrage in AI model markets where arbitrageurs allocate inference budget across competing providers to undercut pricing.
3/25/2026
mmFHE: mmWave Sensing with End-to-End Fully Homomorphic Encryption
First system enabling fully homomorphic encryption for end-to-end mmWave radar sensing with composable FHE kernels for signal processing and ML inference.
3/25/2026
Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
Token-level analysis of distributional shifts during RLVR fine-tuning of LLMs, examining mechanisms underlying reasoning improvements.
3/25/2026
Wake Up to the Past: Using Memory to Model Fluid Wake Effects on Robots
Data-driven approach using memory-augmented neural networks to model fluid wake effects for autonomous aerial and aquatic robots.
3/25/2026
Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architectures
Functional component ablation framework analyzing specialization in hybrid language models combining attention with state space models or linear attention.
3/25/2026
OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection
Verifiable synthetic benchmark for LLM-based insider threat detection using deterministic simulation engine to maintain ground truth and cross-artifact consistency.
3/25/2026
Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling
Differential privacy framework for RLHF fine-tuning that decouples reward learning to preserve user privacy in LLM preference-based training.
3/25/2026
Benchmarking Multi-Agent LLM Architectures for Financial Document Processing: A Comparative Study of Orchestration Patterns, Cost-Accuracy Tradeoffs and Production Scaling Strategies
Systematic benchmark comparing four multi-agent LLM orchestration architectures for financial document processing with cost-accuracy tradeoffs and scaling strategies.
3/25/2026
Improving LLM Predictions via Inter-Layer Structural Encoders
Method leveraging intermediate layer representations in LLMs via Inter-Layer Structural Encoders to improve task-specific predictions beyond final-layer features.
3/25/2026
REALITrees: Rashomon Ensemble Active Learning for Interpretable Trees
Active learning approach using Rashomon ensemble for interpretable decision tree induction with direct hypothesis space characterization.
3/25/2026
KALAVAI: Predicting When Independent Specialist Fusion Works -- A Quantitative Model for Post-Hoc Cooperative LLM Training
Quantitative model predicting when independently fine-tuned specialist LLMs can be fused post-hoc for improved performance using divergence metric.
3/25/2026
Reconstruction-Guided Slot Curriculum: Addressing Object Over-Fragmentation in Video Object-Centric Learning
Method addressing over-fragmentation in video object-centric learning through reconstruction-guided slot curriculum training approach.
3/25/2026
Exposure-Normalized Bed and Chair Fall Rates via Continuous AI Monitoring
Retrospective study using continuous AI monitoring to measure bed and chair fall rates in healthcare settings over exposure time.
3/25/2026
When AI Shows Its Work, Is It Actually Working? Step-Level Evaluation Reveals Frontier Language Models Frequently Bypass Their Own Reasoning
Research on whether LLMs' step-by-step reasoning is genuinely used or post-hoc narrative generation through step-level evaluation of frontier models.
3/25/2026
TorR: Towards Brain-Inspired Task-Oriented Reasoning via Cache-Oriented Algorithm-Architecture Co-design
arXiv paper on brain-inspired object detection co-design. Algorithm-architecture optimization for CLIP-based task-oriented detection on edge devices.
3/25/2026
Dynamical Systems Theory Behind a Hierarchical Reasoning Model
arXiv paper analyzing hierarchical reasoning models for LLMs. Mathematical theory of recursive networks for algorithmic reasoning.
3/25/2026
Off-Policy Evaluation and Learning for Survival Outcomes under Censoring
arXiv paper on off-policy evaluation for survival outcomes with censored data. Applied ML research for decision-making systems.
3/25/2026
Dual-Teacher Distillation with Subnetwork Rectification for Black-Box Domain Adaptation
arXiv paper on black-box domain adaptation using dual-teacher distillation. Technical ML research on knowledge transfer without source access.
3/25/2026
FixationFormer: Direct Utilization of Expert Gaze Trajectories for Chest X-Ray Classification
Computer vision method integrating expert eye gaze trajectories into transformer models for improved chest X-ray classification in radiology.
3/25/2026
Privacy-Preserving EHR Data Transformation via Geometric Operators: A Human-AI Co-Design Technical Report
Human-AI co-design approach for privacy-preserving transformation of electronic health records using geometric operators to enable secure data sharing.
3/25/2026
Stepwise Variational Inference with Vine Copulas
Novel stepwise variational inference method using vine copulas for estimating complex latent dependencies in probabilistic models.
3/25/2026
DariMis: Harm-Aware Modeling for Dari Misinformation Detection on YouTube
Dataset and harm-aware model for Dari-language misinformation detection on YouTube with information type and harm level annotations.
3/25/2026
A Critical Review on the Effectiveness and Privacy Threats of Membership Inference Attacks
Critical review framework evaluating membership inference attacks and conditions under which they pose genuine privacy threats to ML models.
3/25/2026
Can Large Language Models Reason and Optimize Under Constraints?
Investigation of LLMs' reasoning and optimization capabilities under physical and operational constraints using Optimal Power Flow problems.
3/25/2026
YOLOv10 with Kolmogorov-Arnold networks and vision-language foundation models for interpretable object detection and trustworthy multimodal AI in computer vision perception
Object detection framework combining YOLOv10 with Kolmogorov-Arnold networks and vision-language models for interpretability.
3/25/2026
HUydra: Full-Range Lung CT Synthesis via Multiple HU Interval Generative Modelling
Generative AI approach for lung CT synthesis across full Hounsfield Unit range to address medical imaging data scarcity.
3/25/2026
Post-Selection Distributional Model Evaluation
Framework for model evaluation analyzing performance and reliability trade-offs when target KPI levels are unknown.