5/14/2026
Switching Successor Measures for Hierarchical Zero-shot Reinforcement Learning
arXiv paper: Hierarchical reinforcement learning with switching successor measures for zero-shot RL without fixed temporal abstractions.
5/14/2026
Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
arXiv paper: Bilingual pre-training outperforms hyperparameter tuning in data-constrained low-resource language settings.
5/14/2026
Teacher-Guided Policy Optimization for LLM Distillation
arXiv paper: Teacher-Guided Policy Optimization for LLM distillation using Reverse KL to improve student-teacher convergence.
5/14/2026
EMO: Frustratingly Easy Progressive Training of Extendable MoE
arXiv paper: EMO framework for progressive training of Mixture-of-Experts models addressing memory and communication efficiency bottlenecks.
5/14/2026
Unified generalization analysis for physics informed neural networks
arXiv paper: Generalization bounds analysis for Physics-Informed Neural Networks (PINNs) and variational variants.
5/14/2026
Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction
arXiv paper: Chem-GMNet geometric transformer for molecular property prediction using domain-native architecture over generic SMILES models.
5/14/2026
LightSplit: Practical Privacy-Preserving Split Learning via Orthogonal Projections
LightSplit privacy-preserving split learning using orthogonal projections to reduce communication overhead and prevent reconstruction attacks.
5/14/2026
Delightful Exploration
Exploration algorithm balancing uncertainty resolution with action budget using expected improvement and surprisal gating.
5/14/2026
Contextual Bandits for Resource-Constrained Devices using Probabilistic Learning
Contextual bandits algorithm optimized for resource-constrained devices using probabilistic learning.
5/14/2026
Building Interactive Real-Time Agents with Asynchronous I/O and Speculative Tool Calling
Real-time AI agents using asynchronous I/O and speculative tool calling for sub-1-second latency in interactive applications.
5/14/2026
Phasor Memory Networks: Stable Backpropagation Through Time for Scalable Explicit Memory
Phasor Memory Networks architecture enabling stable backpropagation for explicit memory in language models via unitary dynamics.
5/14/2026
Beyond Oversquashing: Understanding Signal Propagation in GNNs Via Observables
Analysis of signal propagation in GNNs addressing information loss through oversmoothing and oversquashing phenomena.
5/14/2026
Teaching and Learning under Deductive Errors
Teaching framework for machine learning that accounts for deductive errors in learners like LLMs during few-shot learning.
5/14/2026
Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation
Adversarial training approach addressing long-tail data imbalance through adaptive perturbations and theoretical analysis.
5/14/2026
The Diffusion Encoder
Novel encoder architecture replacing VAE encoders with diffusion models for improved latent representation learning.
5/14/2026
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
Data augmentation method for offline reinforcement learning using trajectory-based techniques to train models from limited suboptimal data.
5/14/2026
When is Warmstarting Effective for Scaling Language Models?
Research on warmstarting techniques for scaling language models, analyzing initialization constraints and growth strategies for training efficiency.
5/14/2026
DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning
Data-free second-order preconditioning for differentially private deep learning without privacy budget consumption.
5/14/2026
LIFT: Last-Mile Fine-Tuning for Table Explicitation
Pipeline combining pretrained LLM table extraction with fine-tuned small model error repair for low data requirements.
5/14/2026
Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity
Asynchronous SGD with gradient rescaling for distributed optimization under data and system heterogeneity.
5/14/2026
Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy
Flow-based policy for stable and expressive reinforcement learning without backpropagation through solvers.
5/14/2026
Twincher: Bijective Representation Learning for Robust Inversion of Continuous Systems
Bijective representation learning framework for robust inversion of continuous forward processes.
5/14/2026
OSDN: Improving Delta Rule with Provable Online Preconditioning in Linear Attention
Improved delta rule with online preconditioning for linear attention in state-space models.
5/14/2026
Discovery of Hidden Miscalibration Regimes
Method for discovering hidden miscalibration in model confidence across different input types.
5/14/2026
Effective Context in Transformers: An Analysis of Fragmentation and Tokenization
Analysis of how tokenization and representation choices affect transformer context window effectiveness and information exposure.
5/14/2026
HLS-Seek: QoR-Aware Code Generation for High-Level Synthesis via Proxy Comparative Reward Reinforcement Learning
RL-based LLM approach for high-level synthesis code generation using comparative rewards for quality optimization.
5/14/2026
Temper and Tilt Lead to SLOP: Reward Hacking Mitigation with Inference-Time Alignment
Inference-time alignment technique using temperature adjustment to mitigate reward hacking in LLM outputs.
5/14/2026
Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models
Foundation model for dynamic graphs across multiple domains using decoupled prompts for multi-domain pretraining.
5/14/2026
Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
Self-supervised contrastive reinforcement learning algorithm for discrete action spaces without hand-crafted rewards.
5/14/2026
Deep Learning as Neural Low-Degree Filtering: A Spectral Theory of Hierarchical Feature Learning
Neural Low-Degree Filtering (Neural LoFi) provides spectral theory of hierarchical feature learning in gradient-based deep learning.
5/14/2026
Achieving $\epsilon^{-2}$ Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions
Proves first Õ(ε⁻²) sample complexity for single-loop off-policy actor-critic methods under minimal assumptions.
5/14/2026
Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization
Reward-Decorrelated Policy Optimization (RDPO) for multi-task and mixed-reward reinforcement learning with heterogeneous rewards.
5/14/2026
Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training
Geometric and spectral study of low-rank pre-training for LLMs, comparing generalization to full-rank training beyond perplexity.
5/14/2026
Three-Stage Learning Unlocks Strong Performance in Simple Models for Long-Term Time Series Forecasting
Three-stage learning approach for long-term time series forecasting using simple linear models and MLPs without complex architectures.
5/14/2026
Sampling from Flow Language Models via Marginal-Conditioned Bridges
Proposes sampling method for flow language models using marginal-conditioned bridges to preserve posterior marginal structure.
5/14/2026
Scale-Sensitive Shattering: Learnability and Evaluability at Optimal Scale
Establishes scale-sensitive generalization of PAC learning fundamental theorem using fat-shattering dimension at optimal scales.
5/14/2026
A Hierarchical Language Model with Predictable Scaling Laws and Provable Benefits of Reasoning
Analyzes hierarchical synthetic languages with exact k-gram ansatz to derive explicit scaling laws and benefits of reasoning in transformers.
5/14/2026
Polyhedral Instability Governs Regret in Online Learning
Analyzes regret in online learning over combinatorial actions using convex relaxations, governed by polyhedral instability.
5/14/2026
MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling
MILM extends large language models to handle multimodal irregular time series with asynchronous observations and textual channels.
5/14/2026
Tight Sample Complexity Bounds for Entropic Best Policy Identification
Derives tight sample complexity bounds for best-policy identification in risk-sensitive reinforcement learning with entropic risk measures.
5/14/2026
Learning POMDP World Models from Observations with Language-Model Priors
Learns POMDP world models from observation-action trajectories using language model priors for agents in partially observable environments.
5/14/2026
High-Rate Quantized Matrix Multiplication II
Quantized matrix multiplication technique for weight-only post-training quantization of LLMs using available covariance information.
5/14/2026
MinT: Managed Infrastructure for Training and Serving Millions of LLMs
Managed infrastructure system for LoRA post-training and serving of millions of LLM variants using shared base model deployments.
5/14/2026
Attention Once Is All You Need: Efficient Streaming Inference with Stateful Transformers
Stateful transformer architecture for efficient streaming inference with persistent KV cache reducing prefill cost to O(|q|) complexity.
5/14/2026
Improving Reproducibility in Evaluation through Multi-Level Annotator Modeling
Multi-level annotator modeling framework to improve reproducibility of LLM evaluation by accounting for human rater biases and subjectivity.
5/14/2026
Provable Quantization with Randomized Hadamard Transform
Theoretical analysis of vector quantization using randomized Hadamard transform for similarity search, federated learning, and KV cache compression.
5/14/2026
EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering
Entropy-guided approach for efficient test-time scaling of agentic systems on software engineering tasks like code generation and bug fixing.
5/14/2026
Earth Science Foundation Models: From Perception to Reasoning and Discovery
Review of foundation models for Earth science applications integrating multimodal data for perception and scientific discovery tasks.
5/14/2026
Brain Tumor Classification in MRI Images: A Computationally Efficient Convolutional Neural Network
Lightweight CNN for brain tumor classification in MRI images. Medical imaging application.
5/14/2026
On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning
Swin Transformer with federated learning for privacy-preserving UAV image transmission in low-altitude networks.