4/1/2026
Realistic Market Impact Modeling for Reinforcement Learning Trading Environments
Gymnasium-compatible RL trading environments with realistic nonlinear market impact models for agent evaluation.
4/1/2026
HCLSM: Hierarchical Causal Latent State Machines for Object-Centric World Modeling
Hierarchical world model with object-centric decomposition and causal latent dynamics for video prediction.
4/1/2026
Efficient Bilevel Optimization with KFAC-Based Hypergradients
Bilevel optimization using KFAC-based hypergradients for efficient inverse Hessian-vector product computation.
4/1/2026
Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification
Graph coarsening method for scalable Graph Convolutional Networks on large-scale node classification tasks.
4/1/2026
Deep Learning-Based Anomaly Detection in Spacecraft Telemetry on Edge Devices
Three deep learning approaches for spacecraft telemetry anomaly detection optimized for edge device deployment using neural architecture search.
4/1/2026
mtslearn: Machine Learning in Python for Medical Time Series
Open-source Python library for machine learning on medical time-series data, addressing heterogeneous clinical data and reducing friction for ML practitioners in healthcare applications.
4/1/2026
An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms
Lightweight uncertainty quantification for neural networks using gradient norms and isotropy assumption without training data access.
4/1/2026
Survival In-Context: Prior-fitted In-context Learning Tabular Foundation Model for Survival Analysis
Prior-fitted tabular foundation model using in-context learning for survival analysis with limited and censored data.
4/1/2026
Why not to use Cosine Similarity between Label Representations
Analysis showing cosine similarity between label representations in softmax classifiers does not reliably indicate model behavior.
4/1/2026
Target-Aligned Reinforcement Learning
Target-Aligned RL (TARL) framework addressing stability-recency tradeoff in target networks through selective emphasis of aligned transitions.
4/1/2026
Disentangled Graph Prompting for Out-Of-Distribution Detection
Graph prompt-based method for out-of-distribution detection in neural networks using disentangled representations.
4/1/2026
A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
Information decomposition framework measuring information spectrum in vision-language models to assess multimodal fusion vs unimodal priors.
4/1/2026
Mind the Gap: A Framework for Assessing Pitfalls in Multimodal Active Learning
Framework analyzing pitfalls in active learning for multimodal data, addressing missing modalities and varying interaction structures.
4/1/2026
One-for-All: A Lightweight Stabilized and Parameter-Efficient Pre-trained LLM for Time Series Forecasting
One-for-All: parameter-efficient LoRA variant (rsLoRA) for adapting frozen LLMs to multivariate time-series forecasting tasks.
4/1/2026
Training-Free Dynamic Upcycling of Expert Language Models
Training-free method to combine multiple domain-specific expert LLMs into single multi-domain model without fine-tuning.
4/1/2026
Big2Small: A Unifying Neural Network Framework for Model Compression
Big2Small unifies model compression techniques (pruning, quantization, distillation, decomposition) under single mathematical framework.
4/1/2026
From Density Matrices to Phase Transitions in Deep Learning: Spectral Early Warnings and Interpretability
Uses reduced density matrices from quantum chemistry to predict phase transitions in neural networks during training and improve interpretability.
4/1/2026
Loss Gap Parity for Fairness in Heterogeneous Federated Learning
Proposes EAGLE, a federated learning algorithm ensuring fair performance across heterogeneous clients by minimizing loss gap parity.
4/1/2026
Curvature-Guided LoRA: Steering in the pretrained NTK subspace
Curvature-Guided LoRA: Parameter-efficient fine-tuning approach using prediction alignment to match full fine-tuning performance.
4/1/2026
Task Scarcity and Label Leakage in Relational Transfer Learning
Study of label leakage problem in relational transfer learning where task scarcity causes models to learn task-specific shortcuts.
4/1/2026
Real-Time Explanations for Tabular Foundation Models
ShapPFN: Foundation model integrating Shapley value regression for real-time interpretable predictions on tabular data.
4/1/2026
Meteorology-Driven GPT4AP: A Multi-Task Forecasting LLM for Atmospheric Air Pollution in Data-Scarce Settings
GPT4AP: Parameter-efficient multi-task forecasting framework using rsLoRA for air pollution prediction in data-scarce regions.
4/1/2026
Aligning Validation with Deployment: Target-Weighted Cross-Validation for Spatial Prediction
Target-Weighted Cross-Validation method for improving predictive risk estimation in spatial prediction with structured data.
4/1/2026
Tracking Equivalent Mechanistic Interpretations Across Neural Networks
Framework for discovering and validating mechanistic interpretations across neural networks to improve interpretability and generalization.
4/1/2026
Tucker Attention: A generalization of approximate attention mechanisms
Research on Tucker attention as a generalization of approximate attention mechanisms like GQA and MLA using low-rank factorizations.
4/1/2026
Reward-Based Online LLM Routing via NeuralUCB
NeuralUCB-based cost-aware LLM routing algorithm that adapts online to model performance and cost, outperforming supervised routing baselines.
4/1/2026
CRAFT: Cost-aware Expert Replica Allocation with Fine-Grained Layerwise Estimations
CRAFT: Cost-aware expert replica allocation for mixture-of-experts LLM serving with fine-grained layerwise load-balancing estimations.
4/1/2026
Spark-LLM-Eval: A Distributed Framework for Statistically Rigorous Large Language Model Evaluation
Spark-LLM-Eval: Distributed framework for statistically rigorous evaluation of LLMs at scale across hundreds of thousands of samples.
4/1/2026
UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG
UltRAG: Scalable recipe for knowledge graph RAG with LLMs to reduce hallucinations by integrating structured knowledge in context windows.
4/1/2026
DF-ACBlurGAN: Structure-Aware Conditional Generation of Internally Repeated Patterns for Biomaterial Microtopography Design
Conditional GAN for generating biomaterial microtopography with internally repeated periodic patterns and global structural consistency.
4/1/2026
When GPUs Fail Quietly: Observability-Aware Early Warning Beyond Numeric Telemetry
Early warning system for GPU failures using observability and structural signals beyond numeric telemetry for HPC and AI workloads.
4/1/2026
Mitigating Temporal Blindness in Kubernetes Autoscaling: An Attention-Double-LSTM Framework
Attention-LSTM framework for Kubernetes autoscaling addressing temporal blindness in serverless workload orchestration using deep reinforcement learning.
4/1/2026
Generalizable Foundation Models for Calorimetry via Mixtures-of-Experts and Parameter Efficient Fine Tuning
Foundation model for particle physics detector simulation using mixture-of-experts and parameter-efficient fine-tuning inspired by LLM techniques.
4/1/2026
WAter: A Workload-Adaptive Knob Tuning System based on Workload Compression
ML-based database parameter tuning system using workload compression to reduce configuration evaluation cost and improve DBMS performance.
4/1/2026
OptiMer: Optimal Distribution Vector Merging Is Better than Data Mixing for Continual Pre-Training
OptiMer: Method to optimize data mixture ratios for LLM continual pre-training by extracting and merging distribution vectors without fixed hyperparameters.
4/1/2026
Calibrated Fusion for Heterogeneous Graph-Vector Retrieval in Multi-Hop QA
Score calibration method for heterogeneous graph-vector retrieval fusion in multi-hop question answering using percentile-rank normalization.
4/1/2026
Robust Multi-Agent Reinforcement Learning for Small UAS Separation Assurance under GPS Degradation and Spoofing
Multi-agent reinforcement learning approach for unmanned aircraft separation assurance under adversarial GPS degradation and spoofing.
4/1/2026
Minimum Norm Interpolation via The Local Theory of Banach Spaces: The Role of $2$-Uniform Convexity
Theoretical analysis of minimum-norm interpolation under 2-uniform convexity assumptions for understanding generalization in overparameterized neural networks.
4/1/2026
AutoWorld: Scaling Multi-Agent Traffic Simulation with Self-Supervised World Models
Multi-agent traffic simulation framework using self-supervised world models to scale autonomous driving system testing with unlabeled sensor data.
4/1/2026
A Pontryagin Method of Model-based Reinforcement Learning via Hamiltonian Actor-Critic
Model-based reinforcement learning approach using Pontryagin methods and Hamiltonian actor-critic to address compounding model errors in long-horizon value estimation.
4/1/2026
Mimosa Framework: Toward Evolving Multi-Agent Systems for Scientific Research
Mimosa: evolving multi-agent framework for autonomous scientific research that synthesizes and refines LLM-based agent workflows.
4/1/2026
PolarQuant: Optimal Gaussian Weight Quantization via Hadamard Rotation for LLM Compression
PolarQuant: post-training weight quantization method for LLM compression using Hadamard rotation and Gaussian optimization.
4/1/2026
Software Vulnerability Detection Using a Lightweight Graph Neural Network
GNN-based model for software vulnerability detection that offers better scalability than LLM approaches for code analysis tasks.
4/1/2026
Long-Document QA with Chain-of-Structured-Thought and Fine-Tuned SLMs
LiteCoST framework for document QA using chain-of-structured-thought and fine-tuned small language models for high accuracy and low latency.
4/1/2026
The Thiomi Dataset: A Large-Scale Multimodal Corpus for Low-Resource African Languages
Thiomi: large-scale multimodal dataset with 600k+ text annotations and 385k+ audio recordings across 10 African languages.
4/1/2026
MemRerank: Preference Memory for Personalized Product Reranking
MemRerank framework distilling user purchase history into preference signals for personalized LLM-based shopping agent product reranking.
4/1/2026
Beyond Corner Patches: Semantics-Aware Backdoor Attack in Federated Learning
SABLE framework for semantically-aware backdoor attacks in federated learning using realistic, in-distribution triggers.
4/1/2026
Rigorous Explanations for Tree Ensembles
Method for generating rigorous, human-interpretable explanations for tree ensemble model predictions.
4/1/2026
AP-DRL: A Synergistic Algorithm-Hardware Framework for Automatic Task Partitioning of Deep Reinforcement Learning on Versal ACAP
Hardware-software framework for automatic task partitioning of deep reinforcement learning on Xilinx Versal ACAP.
4/1/2026
AGFT: Alignment-Guided Fine-Tuning for Zero-Shot Adversarial Robustness of Vision-Language Models
Fine-tuning framework (AGFT) for improving zero-shot adversarial robustness of vision-language models while preserving alignment.