3/19/2026
Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data
arXiv paper: Restoration Score Distillation framework for learning generative models from corrupted data. Novel ML research.
3/19/2026
Time Tracker: Mixture-of-Experts-Enhanced Foundation Time Series Forecasting Model with Decoupled Training Pipelines
Foundation model for time series forecasting using mixture-of-experts architecture with decoupled training to handle diverse temporal patterns and multi-variable correlations.
3/19/2026
An Introduction to Flow Matching and Diffusion Models
Tutorial on diffusion and flow-based generative models covering mathematical foundations, ODEs, SDEs, and core algorithms for image, video, and multi-modal generation.
3/19/2026
MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning
Offline reinforcement learning method for mismatched dynamics leveraging model-based approaches to explore high-reward states.
3/19/2026
SatSOM: Saturation Self-Organizing Maps for Continual Learning
Self-organizing map extension addressing catastrophic forgetting in continual learning scenarios.
3/19/2026
Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Data
Privacy-preserving neural network framework integrating epidemiological modeling with differential privacy guarantees.
3/19/2026
Knowing What You Cannot Explain: Learning to Reject Low-Quality Explanations
Learning to Reject framework extending ML models to abstain from predictions and explanations with low quality.
3/19/2026
Learning from Oblivion: Predicting Knowledge Overflowed Weights via Retrodiction of Forgetting
Method predicting better pre-trained weights by leveraging structural properties and retrodiction of forgetting.
3/19/2026
Fast weight programming and linear transformers: from machine learning to neurobiology
Fast weight programmers with 2D matrix hidden states connecting RNNs, language modeling, and neurobiology.
3/19/2026
Constraint Learning in Multi-Agent Dynamic Games from Demonstrations of Local Nash Interactions
Inverse game theory algorithm learning constraints from Nash equilibrium demonstrations using MILP formulations.
3/19/2026
Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition
Transfer learning framework for EEG-based emotion recognition using domain-class prototypes.
3/19/2026
Diagonal Linear Networks and the Lasso Regularization Path
Theoretical analysis of implicit regularization in diagonal linear networks via Lasso regularization path.
3/19/2026
Tree Search for LLM Agent Reinforcement Learning
Tree-based group relative policy optimization for LLM agents addressing sparse supervision in multi-turn tasks.
3/19/2026
IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning
Method aligning supervised fine-tuning with in-context learning activations to improve LLM generalization and calibration.
3/19/2026
In-Context Compositional Q-Learning for Offline Reinforcement Learning
Offline reinforcement learning using in-context learning with linear Transformers for compositional Q-function estimation.
3/19/2026
Stable Forgetting: Bounded Parameter-Efficient Unlearning in Foundation Models
Parameter-efficient unlearning method for foundation models addressing privacy/safety with bounded weight growth.
3/19/2026
Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning
Slow-Fast Policy Optimization framework for improving LLM reasoning via reinforcement learning with stable gradient updates.
3/19/2026
Scalable Energy-Based Models via Adversarial Training: Unifying Discrimination and Generation
Energy-based models combining classification and generation via adversarial training to improve SGLD stability.
3/19/2026
Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
Proposes continual low-rank adapters for LLM-based recommender systems handling evolving users and preferences without catastrophic forgetting.
3/19/2026
SoilX: Calibration-Free Comprehensive Soil Sensing through Contrastive Cross-Component Learning
Develops calibration-free soil sensing system using contrastive learning to predict moisture and macronutrients without retraining.
3/19/2026
Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks
Presents augmentation-free graph contrastive learning via fractional-order neural diffusion networks for multi-scale structure learning.
3/19/2026
A robust methodology for long-term sustainability evaluation of Machine Learning models
Proposes standardized methodology for evaluating long-term sustainability and efficiency of ML models addressing Green AI gaps.
3/19/2026
Genomic Next-Token Predictors are In-Context Learners
Demonstrates in-context learning emerges organically in genomic sequence models trained with next-token prediction on DNA sequences.
3/19/2026
Provably Safe Model Updates
Develops methods for provably safe ML model updates preventing catastrophic forgetting and alignment drift in dynamic environments.
3/19/2026
Efficient Cross-Domain Offline Reinforcement Learning with Dynamics- and Value-Aligned Data Filtering
Proposes data filtering method for cross-domain offline RL addressing dynamics misalignment between source and target domains.
3/19/2026
A Comedy of Estimators: On KL Regularization in RL Training of LLMs
Analyzes KL regularization estimators in RL training of LLMs, comparing bias-variance tradeoffs of different approximation methods.
3/19/2026
VL-RouterBench: A Benchmark for Vision-Language Model Routing
VL-RouterBench benchmark for evaluating vision-language model routing systems with quality-cost tradeoff assessment at scale.
3/19/2026
Evaluating Feature Dependent Noise in Preference-based Reinforcement Learning
Evaluates feature-dependent noise in preference-based reinforcement learning with realistic noise patterns correlated to observations.
3/19/2026
GIFT: Reconciling Post-Training Objectives via Finite-Temperature Gibbs Initialization
Proposes GIFT method reconciling SFT and RL post-training for Large Reasoning Models via Gibbs initialization to prevent distributional collapse.
3/19/2026
Global Optimization By Gradient From Hierarchical Score-Matching Spaces
Solves constrained optimization problems via gradient-based methods using hierarchical score-matching spaces to overcome local optima.
3/19/2026
Learning Adaptive Distribution Alignment with Neural Characteristic Function for Graph Domain Adaptation
Proposes neural characteristic function approach for graph domain adaptation addressing distributional shifts without manual feature design.
3/19/2026
Distribution-Free Sequential Prediction with Abstentions
Studies sequential prediction with option to abstain in semi-adversarial settings mixing adversarial and stochastic instances.
3/19/2026
A Deep Surrogate Model for Robust and Generalizable Long-Term Blast Wave Prediction
Creates deep surrogate model for blast wave prediction that generalizes to out-of-distribution urban scenarios using machine learning.
3/19/2026
Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
Develops federated causal representation learning for decentralized counterfactual reasoning across coupled industrial systems while preserving data privacy.
3/19/2026
Detecting Transportation Mode Using Dense Smartphone GPS Trajectories and Transformer Models
Introduces SpeedTransformer, a transformer-based model for detecting transportation modes from smartphone GPS speed data.
3/19/2026
Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
Proposes Hyperparameter Trajectory Inference to adjust neural network hyperparameters post-deployment without full retraining using optimal transport.
3/19/2026
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Studies how pretrained Vision-Language-Action models resist catastrophic forgetting during continual learning in robot policy training.
3/19/2026
Thin Keys, Full Values: Reducing KV Cache via Low-Dimensional Attention Selection
Reduces transformer KV cache by using low-dimensional keys for attention selection while maintaining high-dimensional values, achieving O(log N) dimensional compression.
3/19/2026
JAWS: Enhancing Long-term Rollout of Neural PDE Solvers via Spatially-Adaptive Jacobian Regularization
JAWS improves neural PDE solvers' long-term rollouts using spatially-adaptive Jacobian regularization to prevent spectral blow-up and unphysical divergence.
3/19/2026
Exploiting Adaptive Channel Pruning for Communication-Efficient Split Learning
Adaptive channel pruning technique reduces communication overhead in split learning by selectively transmitting intermediate feature representations.
3/19/2026
Meta-Reinforcement Learning with Self-Reflection for Agentic Search
MR-Search proposes meta-reinforcement learning with self-reflection for agentic search, enabling agents to adapt strategies across episodes and improve in-context exploration.
3/19/2026
Disentangled Representation Learning through Unsupervised Symmetry Group Discovery
Method for embodied agents to autonomously discover symmetry group structure for disentangled representation learning without requiring prior knowledge of group properties.
3/19/2026
Deep learning and the rate of approximation by flows
Theoretical investigation of deep residual networks' approximation capacity in continuous dynamical systems, quantifying minimal time-horizons for diffeomorphism approximation.
3/19/2026
OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
OMNIFLOW is a multimodal agent combining LLMs with physics-grounded reasoning for scientific tasks involving PDEs, addressing hallucinations through cross-domain generalization.
3/19/2026
PhasorFlow: A Python Library for Unit Circle Based Computing
PhasorFlow: open-source Python library for computing on unit circle using complex phasors and unitary wave interference gates.
3/19/2026
Trajectory-Optimized Time Reparameterization for Learning-Compatible Reduced-Order Modeling of Stiff Dynamical Systems
Time reparameterization technique for machine-learning reduced-order models of stiff dynamical systems improving training efficiency.
3/19/2026
The Moral Foundations Reddit Corpus
Reddit corpus annotated with moral sentiment and framing for NLP tasks related to moral language detection and analysis.
3/19/2026
QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources
QFT: quantization-based approach for full-parameter fine-tuning of large language models with limited computational resources.
3/19/2026
Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
Reinforcement learning method for quantum circuit design handling device noise and connectivity constraints on real quantum hardware.
3/19/2026
Byte-token Enhanced Language Models for Temporal Point Processes Analysis
Byte-token enhanced language models for temporal point processes analysis to model event sequences with temporal dynamics and textual descriptions.