3/31/2026
ScoutAttention: Efficient KV Cache Offloading via Layer-Ahead CPU Pre-computation for LLM Inference
ScoutAttention optimizes LLM inference by pre-computing KV cache on CPU ahead of GPU execution to reduce memory constraints.
3/31/2026
Preconditioned Attention: Enhancing Efficiency in Transformers
Preconditioned attention mechanism addressing ill-conditioning in Transformer attention blocks for efficient training.
3/31/2026
GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph
GSR-GNN framework for efficient training of deep graph neural networks on large circuit graphs with memory optimization.
3/31/2026
Online Learning of Kalman Filtering: From Output to State Estimation
Online optimization framework for learning Kalman filtering in partially observed linear dynamical systems with unknown models.
3/31/2026
Hybrid Deep Learning with Temporal Data Augmentation for Accurate Remaining Useful Life Prediction of Lithium-Ion Batteries
CDFormer hybrid deep learning model for lithium-ion battery remaining useful life prediction with temporal data augmentation.
3/31/2026
Omni-Modal Dissonance Benchmark: Systematically Breaking Modality Consensus to Probe Robustness and Calibrated Abstention
OMD-Bench benchmark for testing multimodal model robustness by systematically breaking modality consensus.
3/31/2026
From Inference Routing to Agent Orchestration: Declarative Policy Compilation with Cross-Layer Verification
Semantic Router DSL for declarative LLM inference routing with content signal analysis, privacy policies, and audit traces.
3/31/2026
Scalable Maximum Entropy Population Synthesis via Persistent Contrastive Divergence
GibbsPCDSolver for scalable maximum entropy population synthesis from census data using persistent contrastive divergence.
3/31/2026
Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations
Spectrogram-Enhanced Multimodal Fusion using Vision Transformers for multivariate time series commodity price forecasting.
3/31/2026
Embedding Provenance in Computer Vision Datasets with JSON-LD
JSON-LD metadata framework for embedding provenance information in computer vision datasets.
3/31/2026
Active In-Context Learning for Tabular Foundation Models
Active learning approach for tabular foundation models using in-context learning to reduce cold-start labeling costs.
3/31/2026
Diagnosing Non-Markovian Observations in Reinforcement Learning via Prediction-Based Violation Scoring
Diagnostic method for detecting non-Markovian observation violations in reinforcement learning using prediction-based scoring.
3/31/2026
K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)
K-Means anomaly detection for microcontrollers with distributed model-sharing workflow via Distributed Internet of Learning.
3/31/2026
Conditional Factuality Controlled LLMs with Generalization Certificates via Conformal Sampling
Conditional Factuality Control framework for LLM hallucination control via conformal sampling with conditional coverage guarantees.
3/31/2026
The Geometry of Harmful Intent: Training-Free Anomaly Detection via Angular Deviation in LLM Residual Streams
LatentBiopsy: training-free method detecting harmful prompts by analyzing residual-stream activation geometry in LLMs.
3/31/2026
Kempe Swap K-Means: A Scalable Near-Optimal Solution for Semi-Supervised Clustering
K-Means clustering algorithm with Kempe swaps for semi-supervised constrained clustering under must-link and cannot-link constraints.
3/31/2026
The Geometric Cost of Normalization: Affine Bounds on the Bayesian Complexity of Neural Networks
Theoretical analysis of LayerNorm vs RMSNorm geometric constraints and their effect on neural network Bayesian complexity.
3/31/2026
GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
Image-to-CAD program synthesis using geometric feedback for bootstrapping alignment between visual and symbolic representations.
3/31/2026
FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies
Modular framework and taxonomy for reinforcement learning with diffusion and flow models as policy representations.
3/31/2026
TurboAngle: Near-Lossless KV Cache Compression via Uniform Angle Quantization
KV cache compression via uniform angle quantization in Fast Walsh-Hadamard domain with per-layer precision allocation.
3/31/2026
KV Cache Quantization for Self-Forcing Video Generation: A 33-Method Empirical Study
Empirical study of 33 KV cache quantization methods for self-forcing video generation with memory optimization.
3/31/2026
On Token's Dilemma: Dynamic MoE with Drift-Aware Token Assignment for Continual Learning of Large Vision Language Models
Mixture of Experts with drift-aware token routing for continual instruction tuning of large vision language models.
3/31/2026
Variational Learning of Fractional Posteriors
Variational learning approach for estimating fractional posteriors with applications to probabilistic modeling.
3/31/2026
Decomposing Discrimination: Causal Mediation Analysis for AI-Driven Credit Decisions
Causal mediation analysis framework using Pearl's methods to decompose discrimination in AI-driven credit decisions.
3/31/2026
Match or Replay: Self Imitating Proximal Policy Optimization
Self-imitating proximal policy optimization algorithm improving exploration efficiency in sparse reward reinforcement learning.
3/31/2026
Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization
Binary latent space protein fitness optimization using QUBO-based methods and pretrained protein language models.
3/31/2026
Visualization of Machine Learning Models through Their Spatial and Temporal Listeners
Model-centric visualization framework using spatial and temporal listeners to analyze ML model behaviors.
3/31/2026
Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs
Graph neural network method addressing oversquashing via cross-attentive cohesive subgraph embedding for long-range information.
3/31/2026
BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities
Federated learning framework for multimodal data with heterogeneous clients and missing modalities using block-wise approach.
3/31/2026
An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery
Spiking neural network architecture for energy-efficient predictive insulin delivery on wearable devices.
3/31/2026
On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry
Theoretical analysis of self-supervised pre-training using two-stage M-estimation and representation symmetry to improve bounds.
3/31/2026
Prototype-Aligned Federated Soft-Prompts for Continual Web Personalization
Federated soft-prompts framework for continual web personalization with privacy preservation and stability-plasticity control.
3/31/2026
CrossHGL: A Text-Free Foundation Model for Cross-Domain Heterogeneous Graph Learning
Heterogeneous graph representation learning foundation model for cross-domain transfer without textual attributes or domain-specific schemas.
3/31/2026
Optimizing Coverage and Difficulty in Reinforcement Learning for Quiz Composition
Reinforcement learning agents (DQN, SARSA, A2C/A3C) for automated quiz composition with topic coverage and difficulty optimization.
3/31/2026
Low-Rank Adaptation Reduces Catastrophic Forgetting in Sequential Transformer Encoder Fine-Tuning: Controlled Empirical Evidence and Frozen-Backbone Representation Probes
Empirical study of Low-Rank Adaptation (LoRA) in sequential fine-tuning of transformer encoders, analyzing catastrophic forgetting behavior.
3/31/2026
TMTE: Effective Multimodal Graph Learning with Task-aware Modality and Topology Co-evolution
Multimodal graph learning framework addressing topology quality issues in multimodal-attributed graphs through task-aware co-evolution.
3/31/2026
Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Training
DNNs for detecting smart contract vulnerabilities using contrastive learning and granular-ball training to handle noisy labeled datasets.
3/31/2026
What-If Explanations Over Time: Counterfactuals for Time Series Classification
Survey of counterfactual explanation algorithms for time series classification, covering instance-based, pattern-driven, and gradient-based methods.
3/31/2026
Distributed Online Submodular Maximization under Communication Delays: A Simultaneous Decision-Making Approach
Distributed online algorithm for multi-agent submodular maximization under communication delays for information-gathering in dynamic environments.
3/31/2026
RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
RG-TTA: Meta-controller for test-time adaptation in streaming time series forecasting that modulates adaptation intensity based on regime similarity.
3/31/2026
KVSculpt: KV Cache Compression as Distillation
KVSculpt: KV cache compression for long-context LLM inference treating compression as knowledge distillation, orthogonal to quantization and low-rank methods.
3/31/2026
Stability and Sensitivity Analysis of Relative Temporal-Difference Learning: Extended Version
Stability analysis of relative temporal-difference learning with linear function approximation, establishing convergence conditions when discount factor approaches one.
3/31/2026
Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
Primal-dual policy optimization algorithm for safe reinforcement learning in linear mixture CMDPs with adversarial rewards and unknown transitions.
3/31/2026
Spectral Signatures of Data Quality: Eigenvalue Tail Index as a Diagnostic for Label Noise in Neural Networks
Eigenvalue tail index of neural network weight matrices predicts test accuracy under label noise, achieving R^2=0.984 as diagnostic for data quality.
3/31/2026
ATLAS-RTC: Closing the Loop on LLM Agent Output with Token-Level Runtime Control
ATLAS-RTC: Runtime control system for LLM agents that enforces structured output via token-level monitoring, drift detection, and closed-loop interventions during decoding.
3/31/2026
ITQ3_S: High-Fidelity 3-bit LLM Inference via Interleaved Ternary Quantization with Rotation-Domain Smoothing
ITQ3_S: 3-bit weight quantization method for LLM inference using rotation-domain adaptive quantization to reduce precision loss from weight distribution outliers.
3/31/2026
Physics-Guided Transformer (PGT): Physics-Aware Attention Mechanism for PINNs
Physics-informed neural networks using transformer attention mechanisms for reconstructing continuous fields from sparse observations governed by PDEs.
3/31/2026
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
Proteina-Complexa: fully atomistic protein binder generation method combining conditional generative modeling with structure-based optimization.
3/31/2026
Efficient Inference of Large Vision Language Models
Optimization techniques for efficient inference in large vision-language models addressing computational bottlenecks from high-resolution visual tokens.
3/31/2026
Gradient Manipulation in Distributed Stochastic Gradient Descent with Strategic Agents: Truthful Incentives with Convergence Guarantees
Distributed stochastic gradient descent with game-theoretic incentives to prevent gradient manipulation by strategic agents while ensuring convergence.