3/19/2026
OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
Multimodal LLM agent for physics-informed scientific reasoning, combining language models with PDE solving without domain-specific fine-tuning.
3/19/2026
100x Cost & Latency Reduction: Performance Analysis of AI Query Approximation using Lightweight Proxy Models
Study on using lightweight proxy models to reduce cost and latency of AI queries in SQL, achieving 100x improvements.
3/19/2026
Resource Consumption Threats in Large Language Models
Survey of resource consumption threats in LLMs, covering efficiency issues affecting service capacity, latency, and API costs.
3/19/2026
VisBrowse-Bench: Benchmarking Visual-Native Search for Multimodal Browsing Agents
Benchmark for visual-native search in multimodal browsing agents, evaluating MLLM visual reasoning over web pages.
3/19/2026
Attention-guided Evidence Grounding for Spoken Question Answering
End-to-end spoken question answering framework using attention guidance from speech LLMs for cross-modal alignment without ASR.
3/19/2026
EngGPT2: Sovereign, Efficient and Open Intelligence
Italian open-source LLM with 16B parameters achieving competitive performance on benchmarks while requiring fraction of inference power.
3/19/2026
When Openclaw Agents Learn from Each Other: Insights from Emergent AI Agent Communities for Human-AI Partnership in Education
Studies emergent learning behaviors in ecosystem of 167,000 AI agents interacting as peers across platforms without intervention.
3/19/2026
DexGrasp-Zero: A Morphology-Aligned Policy for Zero-Shot Cross-Embodiment Dexterous Grasping
Zero-shot cross-embodiment dexterous grasping policy using morphology-aligned approach for diverse robotic hands.
3/19/2026
Federated Multi Agent Deep Learning and Neural Networks for Advanced Distributed Sensing in Wireless Networks
Overview of multi-agent deep learning and federated training for distributed sensing in 5G/6G wireless networks.
3/19/2026
Multi-Agent Reinforcement Learning for Dynamic Pricing: Balancing Profitability,Stability and Fairness
Empirical evaluation of multi-agent RL algorithms (MAPPO, MADDPG) for dynamic pricing in competitive markets.
3/19/2026
From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning
Production framework for reliable Arabic function-calling models enabling agentic AI systems through data-centric fine-tuning.
3/19/2026
HoloByte: Continuous Hyperspherical Distillation for Tokenizer-Free Modeling
Tokenizer-free sequence modeling using continuous hyperspherical distillation to preserve byte-level continuity without discrete quantization.
3/19/2026
MHPO: Modulated Hazard-aware Policy Optimization for Stable Reinforcement Learning
Proposes modulated hazard-aware policy optimization to improve training stability in GRPO-based reinforcement learning frameworks.
3/19/2026
Integrating Inductive Biases in Transformers via Distillation for Financial Time Series Forecasting
Addresses transformer limitations for financial time-series forecasting by integrating inductive biases via distillation.
3/19/2026
Transformers Can Learn Rules They've Never Seen: Proof of Computation Beyond Interpolation
Tests whether transformers can learn unseen rules beyond interpolation using controlled experiments with symbolic derivations.
3/19/2026
Do Understanding and Generation Fight? A Diagnostic Study of DPO for Unified Multimodal Models
Systematic study of DPO alignment on unified multimodal models, finding generation quality resists alignment while understanding improves.
3/19/2026
SCE-LITE-HQ: Smooth visual counterfactual explanations with generative foundation models
Proposes counterfactual explanation method using generative foundation models for interpreting neural network predictions in visual domains.
3/19/2026
Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization
Investigates vector quantization in generative models, proposing early quantization to address codebook diversity issues in tokenization for LLMs and diffusion models.
3/19/2026
PRISM: Demystifying Retention and Interaction in Mid-Training
PRISM empirical study of mid-training for LLMs across 7 models showing consistent +15 to +40 point gains on benchmarks with 27B tokens.
3/19/2026
CircuitBuilder: From Polynomials to Circuits via Reinforcement Learning
Applies reinforcement learning with AlphaZero-style training to discover efficient arithmetic circuits for polynomial computation.
3/19/2026
SENSE: Efficient EEG-to-Text via Privacy-Preserving Semantic Retrieval
Proposes privacy-preserving EEG-to-text system using semantic retrieval instead of fine-tuning LLMs for brain-computer interfaces.
3/19/2026
Contextual Preference Distribution Learning
Proposes pipeline to learn context-dependent preference distributions for risk-averse decision-making via inverse optimization.
3/19/2026
REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge
Introduces regression-aware RL method for LLM-as-a-Judge that leverages ordinal structure in scoring tasks.
3/19/2026
Noise-Response Calibration: A Causal Intervention Protocol for LLM-Judges
Proposes calibration protocol for LLM-judges using controlled noise interventions to improve reliability in low-label settings.
3/19/2026
Domain-informed explainable boosting machines for trustworthy lateral spread predictions
Develops domain-informed framework for explainable boosting machines ensuring physical consistency in natural hazard prediction.
3/19/2026
MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild
MetaClaw enables LLM agents to continuously adapt and evolve in production by meta-learning from diverse task distributions without storing raw trajectories.
3/19/2026
Self-Conditioned Denoising for Atomistic Representation Learning
Introduces self-supervised pretraining strategy using denoising for atomistic foundation models in physical sciences.
3/19/2026
Abstraction as a Memory-Efficient Inductive Bias for Continual Learning
Proposes Abstraction-Augmented Training for continual learning to prevent catastrophic forgetting in non-stationary environments.
3/19/2026
Catching rationalization in the act: detecting motivated reasoning before and after CoT via activation probing
Studies motivated reasoning in LLMs using activation probing to detect when chain-of-thought rationalizations don't reflect actual decision factors.
3/19/2026
Variational Rectification Inference for Learning with Noisy Labels
Proposes variational inference approach to handle label noise in deep learning via probabilistic meta-learning.
3/19/2026
Classifier Pooling for Modern Ordinal Classification
Presents model-agnostic ordinal classification method with open-source Python package for clinical and domain applications.
3/19/2026
WINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault Adaptation
Introduces WINFlowNets to improve Generative Flow Networks training for robotics and fault adaptation without pre-training requirements.
3/19/2026
Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity
arXiv: NSDS - calibration-free layer-wise mixed-precision quantization for model compression. Uses dual numerical-structural sensitivity for extreme low-bit quantization.
3/19/2026
Variational Kernel Design for Internal Noise: Gaussian Chaos Noise, Representation Compatibility, and Reliable Deep Learning
arXiv: Variational Kernel Design framework for internal noise in deep networks. Determines optimal correlation geometry and representation compatibility.
3/19/2026
Efficient Exploration at Scale
arXiv: Online learning algorithm for RLHF that improves data efficiency. Incrementally updates reward and language models from choice data.
3/19/2026
SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
Scalable conditional transport method for predicting cellular responses to perturbations in virtual cell models, addressing training efficiency and high-dimensional sparse data challenges.
3/19/2026
Cohomological Obstructions to Global Counterfactuals: A Sheaf-Theoretic Foundation for Generative Causal Models
Sheaf-theoretic foundation formalizing structural causal models in generative models, proving global counterfactual coherence fails with non-trivial causal graph homology.
3/19/2026
Causal Representation Learning on High-Dimensional Data: Benchmarks, Reproducibility, and Evaluation Metrics
Benchmark and evaluation framework for causal representation learning models that transform high-dimensional data into latent spaces for counterfactual generation.
3/19/2026
The Phasor Transformer: Resolving Attention Bottlenecks on the Unit Circle
Phasor Transformer replaces dot-product attention with phase-native operations on unit circle for efficient long-context sequence modeling.
3/19/2026
Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
Baguan-TS integrates raw sequence representation learning with in-context learning using 3D Transformers for time series forecasting.
3/19/2026
Efficient Soft Actor-Critic with LLM-Based Action-Level Guidance for Continuous Control
GuidedSAC reinforcement learning algorithm uses LLMs as action-level supervisors to guide exploration in continuous control tasks.
3/19/2026
Auto-Unrolled Proximal Gradient Descent: An AutoML Approach to Interpretable Waveform Optimization
AutoML approach using deep unfolding of proximal gradient descent for wireless beamforming and waveform optimization.
3/19/2026
QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
QuantFL framework combines federated learning with pre-trained model quantization to reduce energy consumption on IoT edge devices.
3/19/2026
Anisotropic Permeability Tensor Prediction from Porous Media Microstructure via Physics-Informed Progressive Transfer Learning with Hybrid CNN-Transformer
Physics-informed CNN-Transformer hybrid model for predicting permeability tensors from porous media images, replacing expensive simulations.
3/19/2026
CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments
arXiv paper on CLeAN, continual learning normalization method addressing data normalization in dynamic environments for model stability.
3/19/2026
Conditional Inverse Learning of Time-Varying Reproduction Numbers Inference
arXiv paper on conditional inverse learning for estimating time-varying reproduction numbers from epidemic data without structural assumptions.
3/19/2026
FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models
arXiv paper on FoMo X, modular explainability framework for tabular foundation models in outlier detection with interpretable signals.
3/19/2026
Identifying Latent Actions and Dynamics from Offline Data via Demonstrator Diversity
arXiv paper on recovering latent actions and environment dynamics from offline trajectories with action-free data tagged by demonstrator identity.
3/19/2026
AdaMuS: Adaptive Multi-view Sparsity Learning for Dimensionally Unbalanced Data
arXiv paper on AdaMuS, adaptive multi-view sparsity learning for dimensionally unbalanced data in tasks like emotion recognition.
3/19/2026
Complementary Reinforcement Learning
arXiv paper on complementary reinforcement learning for LLM-based agents, improving sample efficiency by leveraging historical experience across episodes.