4/1/2026
MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models
MDM-Prime-v2: Improvements to masked diffusion language models through binary encoding and index shuffling.
4/1/2026
AdaMuS: Adaptive Multi-view Sparsity Learning for Dimensionally Unbalanced Data
Multi-view learning framework handling dimensional disparities across different feature views.
4/1/2026
FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
Federated learning approach using representation geometry to handle noisy annotations in distributed scenarios.
4/1/2026
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
FIPO: RL algorithm improving token-level credit assignment for reasoning in LLMs beyond outcome-based rewards.
4/1/2026
Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning
Safety-aware offline RL method using budget-conditioned reachability analysis for constrained decision-making.
4/1/2026
SkillRouter: Skill Routing for LLM Agents at Scale
SkillRouter: System for routing LLM agent requests to relevant skills from large skill libraries at inference time.
4/1/2026
Cost-Sensitive Neighborhood Aggregation for Heterophilous Graphs: When Does Per-Edge Routing Help?
GNN layer using cost-sensitive neighborhood aggregation for heterophilous graph classification.
4/1/2026
Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback
Theoretical analysis of online convex optimization with two-point bandit feedback and high-probability regret bounds.
4/1/2026
Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs
GNN architecture addressing oversquashing through cross-attentive cohesive subgraph embedding.
4/1/2026
ITQ3_S: High-Fidelity 3-bit LLM Inference via Interleaved Ternary Quantization with Rotation-Domain Smoothing
ITQ3_S: 3-bit LLM quantization method using interleaved ternary quantization and rotation-domain smoothing for efficient inference.
4/1/2026
Principal Prototype Analysis on Manifold for Interpretable Reinforcement Learning
Interpretability method for reinforcement learning using principal prototype analysis on manifolds.
4/1/2026
Neural Federated Learning for Livestock Growth Prediction
Federated learning approach for livestock growth prediction addressing privacy and data scarcity in farm management.
4/1/2026
Quadratic Gradient: A Unified Framework Bridging Gradient Descent and Newton-Type Methods by Synthesizing Hessians and Gradients
Framework unifying gradient descent and Newton-type methods through quadratic gradient with synthesized Hessians.
4/1/2026
Cheap Bootstrap for Fast Uncertainty Quantification of Stochastic Gradient Descent
Methods for uncertainty quantification in stochastic gradient descent using cheap resampling-based confidence intervals.
4/1/2026
Exploring Prime Number Classification: Achieving High Recall Rate and Rapid Convergence with Sparse Encoding
Neural network approach for prime number classification using sparse encoding.
4/1/2026
Measuring the Predictability of Recommender Systems using Structural Complexity Metrics
Metrics for measuring predictability of recommender systems via structural complexity analysis.
4/1/2026
Image-Specific Adaptation of Transformer Encoders for Compute-Efficient Segmentation
Vision transformer optimization for image segmentation with adaptive computation per input image.
4/1/2026
EventChat: Implementation and user-centric evaluation of a large language model-driven conversational recommender system for exploring leisure events in an SME context
LLM-driven conversational recommender system for leisure event discovery with user-centric evaluation in SME context.
4/1/2026
Image Segmentation via Divisive Normalization: dealing with environmental diversity
Image segmentation approach using divisive normalization for autonomous driving under diverse environmental conditions.
4/1/2026
Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations
Framework for tightening convex relaxations of trained neural networks with convex and S-shaped activations for optimization incorporation.
4/1/2026
Real-Time Operator Takeover for Visuomotor Diffusion Policy Training
Real-time operator takeover paradigm allowing seamless human intervention and correction during visuomotor diffusion policy execution.
4/1/2026
DeepRV: Accelerating Spatiotemporal Inference with Pre-trained Neural Priors
Neural network method combining Gaussian processes with pre-trained priors to accelerate spatiotemporal inference on large datasets.
4/1/2026
Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation
German-language LLM pre-training dataset curated via heuristic filtering, model-based selection, and synthetic data generation.
4/1/2026
LLM-Meta-SR: In-Context Learning for Evolving Selection Operators in Symbolic Regression
Meta-learning framework using LLMs to automatically design selection operators for evolutionary symbolic regression algorithms.
4/1/2026
AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models
AVA-Bench systematically evaluates atomic visual abilities of vision foundation models independent of LLM instruction tuning.
4/1/2026
Accelerating Diffusion Large Language Models with SlowFast Sampling: The Three Golden Principles
SlowFast Sampling optimizes inference efficiency in diffusion-based language models through dynamic, flexible token generation strategies.
4/1/2026
Streaming 4D Visual Geometry Transformer
Streaming transformer architecture inspired by autoregressive LLMs for real-time 3D geometry perception and reconstruction from video.
4/1/2026
Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing
Statistical methods for constructing confidence intervals for optimal treatment policy values using softmax smoothing in causal inference.
4/1/2026
NES: An Instruction-Free, Low-Latency Next Edit Suggestion Framework Powered by Learned Historical Editing Trajectories
NES is an instruction-free code editing framework that learns from historical editing trajectories to suggest next edits with low latency.
4/1/2026
TTA-DAME: Test-Time Adaptation with Domain Augmentation and Model Ensemble for Dynamic Driving Conditions
Test-time adaptation method using domain augmentation and model ensembles to handle weather-related domain shifts in autonomous driving.
4/1/2026
Multi-Level Knowledge Distillation and Dynamic Self-Supervised Learning for Continual Learning
Knowledge distillation and self-supervised learning approach for continual learning with class-incremental learning and external unlabeled data.
4/1/2026
A Machine Learning Based Explainability Framework for Interpreting Swarm Intelligence
Interpretability framework for understanding how components of particle swarm optimization algorithms affect performance.
4/1/2026
ORIC: Benchmarking Object Recognition under Contextual Incongruity in Large Vision-Language Models
Benchmark evaluating how large vision-language models handle object recognition in contextually incongruent scenes and manage uncertainty.
4/1/2026
Joint Cooperative and Non-Cooperative Localization in WSNs with Distributed Scaled Proximal ADMM Algorithms
Wireless sensor network localization using distributed optimization algorithms for cooperative and non-cooperative positioning.
4/1/2026
ProxyAttn: Guided Sparse Attention via Representative Heads
ProxyAttn method using representative attention heads to enable efficient sparse attention in LLMs for long-text processing with minimal performance degradation.
4/1/2026
MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Multi-Stream Generative Policy framework for robot learning that combines multiple object-centric policies at inference to improve sample efficiency and generalization.
4/1/2026
Smooth Quasar-Convex Optimization with Constraints
Algorithm for smooth quasar-convex optimization with general convex constraints achieving nearly optimal first-order query complexity.
4/1/2026
Align Your Query: Representation Alignment for Multimodality Medical Object Detection
Representation alignment technique for multimodal medical object detection addressing heterogeneous statistics across imaging modalities.
4/1/2026
TransFIRA: Transfer Learning for Face Image Recognizability Assessment
Transfer learning approach for assessing face image recognizability in unconstrained conditions without relying on visual heuristics.
4/1/2026
Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts
Neuro-symbolic AI overview connecting neural networks with symbolic reasoning to satisfy constraints, addressing reliable trustworthy AI development.
4/1/2026
Local Causal Discovery for Statistically Efficient Causal Inference
Efficient local causal discovery method for identifying adjustment sets without learning the full causal graph.
4/1/2026
Drift Estimation for Diffusion Processes Using Neural Networks Based on Discretely Observed Independent Paths
Nonparametric neural network-based method for drift function estimation in diffusion processes with convergence rate analysis.
4/1/2026
VLA Models Are More Generalizable Than You Think: Revisiting Physical and Spatial Modeling
One-shot adaptation framework improving vision-language-action model generalization to novel camera viewpoints through spatial representation recalibration.
4/1/2026
Script Gap: Evaluating LLM Triage on Indian Languages in Native vs Romanized Scripts in a Real World Setting
Evaluation of LLM performance on Indian language maternal healthcare triage, comparing native scripts versus romanized text in real-world deployment.
4/1/2026
Guiding a Diffusion Transformer with the Internal Dynamics of Itself
Guidance strategy for diffusion transformers using internal model dynamics to improve image generation quality without external classifiers.
4/1/2026
Unsupervised Modular Adaptive Region Growing and RegionMix Classification for Wind Turbine Segmentation
Unsupervised segmentation approach for wind turbine blade inspection using region growing and classification without significant AI/ML innovation.
4/1/2026
Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype
Explainable AI framework using multiple instance learning for survival prediction from glioblastoma histomorphology images without code or tool contributions.
4/1/2026
The Geometry of Thought: How Scale Restructures Reasoning In Large Language Models
Analysis of 25k chain-of-thought trajectories showing neural scaling triggers domain-specific phase transitions in reasoning rather than uniform capability improvements across 8B-70B parameter models.
4/1/2026
$V_0$: A Generalist Value Model for Any Policy at State Zero
V0 is a generalist value model for policy gradient methods that scales efficiently with LLM training, replacing large critic models in actor-critic methods like PPO.
4/1/2026
When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance
Test-time guidance technique for diffusion models enabling fast text-driven image and video editing through inpainting with reduced computational cost.