3/26/2026
Evolutionarily Stable Stackelberg Equilibrium
Domain-grounded tiered retrieval architecture to reduce LLM hallucinations through retrieval-based verification.
3/26/2026
Ontology-Guided Diffusion for Zero-Shot Visual Sim2Real Transfer
Evolutionarily Stable Stackelberg Equilibrium: game theory solution concept for asymmetric leader-follower games.
3/26/2026
Agent Control Protocol: Admission Control for Agent Actions
Ontology-Guided Diffusion for zero-shot sim2real transfer using neuro-symbolic approach to bridge simulation-reality gap.
3/26/2026
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
Agent Control Protocol: formal specification for admission control governance of autonomous agents with cryptographic identity and policy compliance.
3/26/2026
An Agentic Multi-Agent Architecture for Cybersecurity Risk Management
Multi-agent AI system with six specialized agents for automated NIST CSF-aligned cybersecurity risk assessments for small organizations.
3/26/2026
Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models
Study showing finetuning bypasses LLM safety mechanisms and triggers verbatim recall of copyrighted training data.
3/26/2026
DeepXplain: XAI-Guided Autonomous Defense Against Multi-Stage APT Campaigns
Explainable DRL framework for autonomous APT defense using provenance-based graphs and stage-aware modeling.
3/26/2026
LLM-Powered Workflow Optimization for Multidisciplinary Software Development: An Automotive Industry Case Study
LLM-based workflow system for multidisciplinary software development coordinating domain experts and developers in automotive.
3/26/2026
PRISM: Breaking the O(n) Memory Wall in Long-Context LLM Inference via O(1) Photonic Block Selection
PRISM photonic accelerator approach reducing KV cache memory bandwidth from O(n) to O(1) for long-context LLM inference.
3/26/2026
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
mSFT algorithm for optimizing heterogeneous multi-task SFT data mixtures by dynamically adjusting compute per sub-dataset.
3/26/2026
Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors
Weather prediction combining radar observations with foundation model priors for extended nowcasting horizons.
3/26/2026
Sim-to-Real of Humanoid Locomotion Policies via Joint Torque Space Perturbation Injection
Sim-to-real transfer for humanoid robot control using state-dependent joint torque perturbations instead of domain randomization.
3/26/2026
Tiny Inference-Time Scaling with Latent Verifiers
Inference-time scaling with lightweight latent verifiers instead of MLLMs to reduce computational cost in verification.
3/26/2026
Language Models Can Explain Visual Features via Steering
Method using causal interventions and Vision-Language Models to explain sparse autoencoder features in vision models.
3/26/2026
Beyond Accuracy: Introducing a Symbolic-Mechanistic Approach to Interpretable Evaluation
Interpretable evaluation combining symbolic rules with mechanistic interpretability to detect memorization vs genuine generalization.
3/26/2026
Implicit Turn-Wise Policy Optimization for Proactive User-LLM Interaction
ITPO framework for optimizing multi-turn human-LLM interactions via RL despite sparse rewards and user stochasticity.
3/26/2026
Upper Entropy for 2-Monotone Lower Probabilities
Theoretical analysis of upper entropy computation for credal sets and uncertainty quantification. Pure mathematics focus.
3/26/2026
Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG
Training method combining synthetic QA and document generation to improve LLM knowledge beyond RAG performance ceiling.
3/26/2026
Safe Reinforcement Learning with Preference-based Constraint Inference
Safe reinforcement learning framework inferring constraints from user preferences with minimal expert demonstrations.
3/26/2026
AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization
RL agent optimizing operator kernels on Huawei Ascend NPUs. Addresses knowledge gap in alternative hardware ecosystem.
3/26/2026
Causal Reconstruction of Sentiment Signals from Sparse News Data
Causal signal reconstruction approach for converting sparse news sentiment into reliable time series for financial/tech analysis.
3/26/2026
StateLinFormer: Stateful Training Enhancing Long-term Memory in Navigation
StateLinFormer model using linear attention for navigation agents with long-term memory. Addresses context window limitations in Transformers.
3/26/2026
Dual-Criterion Curriculum Learning: Application to Temporal Data
Research on curriculum learning with dual criteria for temporal data. Proposes improved difficulty-based training scheduling.
3/26/2026
PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning
PoiCGAN: Poisoning attack method against federated learning systems using feature-label joint perturbation.
3/26/2026
APreQEL: Adaptive Mixed Precision Quantization For Edge LLMs
APreQEL: Adaptive mixed precision quantization technique for deploying large language models on edge devices with reduced memory and computational requirements.
3/26/2026
The Geometric Price of Discrete Logic: Context-driven Manifold Dynamics of Number Representations
Research on how LLMs form discrete decision boundaries within continuous semantic spaces through context-driven topological distortion of number representations.
3/26/2026
MetaKube: An Experience-Aware LLM Framework for Kubernetes Failure Diagnosis
MetaKube: LLM framework for Kubernetes failure diagnosis with Episodic Pattern Memory Network that learns from operational history to improve diagnostic accuracy over time.
3/26/2026
A Theory of LLM Information Susceptibility
Theoretical framework analyzing fundamental performance limits when deploying fixed LLMs as optimization modules in agentic systems.
3/26/2026
Steering Code LLMs with Activation Directions for Language and Library Control
Method for steering code LLMs via activation space manipulation to control programming language and library preferences at inference time.
3/26/2026
CDMT-EHR: A Continuous-Time Diffusion Framework for Generating Mixed-Type Time-Series Electronic Health Records
Continuous-time diffusion model for generating synthetic electronic health records with mixed numerical and categorical features.
3/26/2026
BXRL: Behavior-Explainable Reinforcement Learning
Framework for generating interpretable explanations of learned behaviors in RL agents with formal behavior definition.
3/26/2026
Self Paced Gaussian Contextual Reinforcement Learning
Curriculum learning approach for contextual RL using closed-form updates for self-paced task sequencing.
3/26/2026
Lightweight Fairness for LLM-Based Recommendations via Kernelized Projection and Gated Adapters
Lightweight fairness method for LLM-based recommenders using kernelized projection and adapters without fine-tuning.
3/26/2026
Probabilistic Geometric Alignment via Bayesian Latent Transport for Domain-Adaptive Foundation Models
Domain adaptation framework for foundation models using probabilistic geometric alignment and Bayesian transport.
3/26/2026
Latent Algorithmic Structure Precedes Grokking: A Mechanistic Study of ReLU MLPs on Modular Arithmetic
Mechanistic analysis of grokking phenomenon in ReLU MLPs on modular arithmetic revealing algorithmic structure.
3/26/2026
Manifold Generalization Provably Proceeds Memorization in Diffusion Models
Theoretical study showing diffusion models learn manifold geometry before memorization under manifold hypothesis.
3/26/2026
Resolving gradient pathology in physics-informed epidemiological models
Solution for training instability in physics-informed neural networks on epidemiological models by addressing gradient pathology.
3/26/2026
Deep Neural Regression Collapse
Analysis of neural collapse phenomenon in regression models across multiple layers showing low-rank structure.
3/26/2026
Unveiling Hidden Convexity in Deep Learning: a Sparse Signal Processing Perspective
Theoretical analysis revealing convex equivalences in ReLU neural networks from sparse signal processing perspective.
3/26/2026
Symbolic--KAN: Kolmogorov-Arnold Networks with Discrete Symbolic Structure for Interpretable Learning
Kolmogorov-Arnold networks combining neural learning with symbolic structure for interpretable scientific equation discovery.
3/26/2026
Why the Maximum Second Derivative of Activations Matters for Adversarial Robustness
Analysis of activation function curvature role in adversarial robustness using parameterized activation family.
3/26/2026
Can VLMs Reason Robustly? A Neuro-Symbolic Investigation
Study of vision-language models' robustness to distribution shifts in visual deductive reasoning tasks.
3/26/2026
HDPO: Hybrid Distillation Policy Optimization via Privileged Self-Distillation
Training method for LLMs on mathematical reasoning combining RL with privileged self-distillation to improve learning on hard problems.
3/26/2026
The Luna Bound Propagator for Formal Analysis of Neural Networks
C++ implementation of neural network verification tool supporting bound propagation methods for DNN formal analysis.
3/26/2026
Off-Policy Safe Reinforcement Learning with Constrained Optimistic Exploration
Safe reinforcement learning method addressing constraint violations in off-policy exploration through constrained optimistic exploration Q-learning.
3/26/2026
Diet Your LLM: Dimension-wise Global Pruning of LLMs via Merging Task-specific Importance Score
DIET: structured pruning method for LLMs using dimension-wise global importance scores that adapt to task-specific requirements.
3/26/2026
Can we generate portable representations for clinical time series data using LLMs?
Uses LLMs to generate portable patient embeddings from clinical time series that transfer across hospitals with minimal retraining.
3/26/2026
Understanding the Challenges in Iterative Generative Optimization with LLMs
Analysis of design challenges in iterative generative optimization using LLMs for self-improving agents; identifies hidden choices engineers must make.
3/26/2026
Stochastic Dimension-Free Zeroth-Order Estimator for High-Dimensional and High-Order PINNs
Dimension-free zeroth-order estimator for PINNs addressing spatial derivative complexity and memory overhead in high-dimensional PDEs.
3/26/2026
i-IF-Learn: Iterative Feature Selection and Unsupervised Learning for High-Dimensional Complex Data
Iterative unsupervised framework for feature selection and clustering in high-dimensional data by recovering influential features.