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A Large-Scale, Cross-Disciplinary Corpus of Systematic Reviews

arXiv:2604.22864v1 Announce Type: cross Abstract: Existing benchmarks for systematic reviewing remain limited either in scale or in disciplinary coverage, with some collections comprising only a modes

researcharxiv-cs-cl

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A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning

DGX agent

arXiv:2604.23225v1 Announce Type: new Abstract: This paper investigates the deep learning optimization problem with softmax cross-entropy loss. We propose a layer separation strategy to alleviate the

researcharxiv-cs-lg

28 Apr 2026

A Lightweight Explainable Guardrail for Prompt Safety

arXiv:2602.15853v2 Announce Type: replace-cross Abstract: We propose a lightweight explainable guardrail (LEG) method to detect unsafe prompts. LEG uses a multi-task learning architecture to jointly l

A Lightweight Toggleable Adhesion Prototype for Multirotor UAV Landing on Tilting Platforms

arXiv:2604.23074v1 Announce Type: new Abstract: Autonomous multirotor landings on uncrewed surface vessels (USVs) are critical for persistent maritime operations but remain challenging due to wave-ind

agentsarxiv-cs-ro

A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws

model-releasesarxiv-cs-lg

arXiv:2604.24037v1 Announce Type: new Abstract: Emergent intelligence have played a major role in the modern AI development. While existing studies primarily rely on empirical observations to characte

A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks

arXiv:2507.16079v2 Announce Type: replace-cross Abstract: With the advancement of deep learning, reducing computational complexity and memory consumption has become a critical challenge, and ternary n

A Milestone in Formalization: The Sphere Packing Problem in Dimension 8

arXiv:2604.23468v1 Announce Type: cross Abstract: In 2016, Viazovska famously solved the sphere packing problem in dimension 8, using modular forms to construct a 'magic' function satisfying optimalit

Local Ai

A Mixture of Experts Vision Transformer for High-Fidelity Surface Code Decoding

arXiv:2601.12483v2 Announce Type: replace-cross Abstract: Quantum error correction is a key ingredient for large scale quantum computation, protecting logical information from physical noise by encodi

local-aiarxiv-cs-lg

A Multi-Dimensional Audit of Politically Aligned Large Language Models

arXiv:2604.24429v1 Announce Type: new Abstract: As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse

safetyarxiv-cs-cl

A Parametric Memory Head for Continual Generative Retrieval

arXiv:2604.23388v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) consolidates retrieval into a single neural model that decodes document identifiers (docids) directly from qu

A Pose-only Geometric Constraint for Multi-Camera Pose Adjustment

model-releasesarxiv-cs-cv

arXiv:2604.23704v1 Announce Type: new Abstract: Multi-camera systems offer rich observation capabilities for visual navigation and 3D scene reconstruction; however, the resulting feature redundancy of

A Reconfigured Wheel-Legged Robot for Enhanced Steering and Adaptability

arXiv:2507.22345v2 Announce Type: replace Abstract: Wheel-legged robots integrate leg agility on rough terrain with wheel efficiency on flat ground. However, most existing designs do not fully capital

researcharxiv-cs-ro

A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning

arXiv:2604.24532v1 Announce Type: new Abstract: Many sequential decision-making tasks involve optimizing multiple conflicting objectives, requiring policies that adapt to different user preferences. I

safetyarxiv-cs-lg

A satellite foundation model for improved wealth monitoring

model-releasesarxiv-cs-cv

arXiv:2604.23166v1 Announce Type: cross Abstract: Poverty statistics guide social policy, but in many low- and middle-income countries, censuses and household surveys that collect these data are costl

A Self-Supervised Framework for Space Object Behaviour Characterisation

arXiv:2504.06176v3 Announce Type: replace-cross Abstract: Foundation Models, which leverage large neural networks pre-trained on unlabelled data before fine-tuning for specific tasks, are increasingly

A Specialized Importance-Aware Quantum Convolutional Neural Network with Ring-Topology (IA-QCNN) for MGMT Promoter Methylation Prediction in Glioblastoma

arXiv:2604.22877v1 Announce Type: cross Abstract: GBM is a highly aggressive primary malignancy in adults, necessitating personalized therapeutic strategies due to its inherent molecular heterogeneity

A successful onboarding as a new employee at Runway requires you be able to properly identify each of these characters and their lore. If yo…

industrycristobal-valenzuela--x

This post discusses the importance of understanding character identification and lore as part of employee onboarding at Runway, likely referencing key figures or mascots associated with the company's

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations

arXiv:2604.24468v1 Announce Type: cross Abstract: Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource

researcharxiv-cs-cl

A Synergistic CNN-Transformer Network with Pooling Attention Fusion for Hyperspectral Image Classification

arXiv:2604.23622v1 Announce Type: new Abstract: In the hyperspectral image (HSI) classification task, each pixel is categorized into a specific land-cover category or material. Convolutional neural ne

A Systematic Approach for Large Language Models Debugging

arXiv:2604.23027v1 Announce Type: new Abstract: Large language models (LLMs) have become central to modern AI workflows, powering applications from open-ended text generation to complex agent-based re

agentsarxiv-cs-ai

A systematic evaluation of vision-language models for observational astronomical reasoning tasks

arXiv:2604.24589v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astro

A Tale of Two Variances: When Single-Seed Benchmarks Fail in Bayesian Deep Learning

arXiv:2604.23114v1 Announce Type: new Abstract: In limited-data settings, a single endpoint mean of an evaluation metric such as the Continuous Ranked Probability Score (CRPS) is itself a random varia

A Taxonomy and Resolution Strategy for Client-Level Disagreements in Federated Learning

arXiv:2604.23386v1 Announce Type: cross Abstract: Federated Learning (FL) typically assumes unconditional collaboration, a premise that overlooks the complexities of real-world, multi-stakeholder envi

A Theoretical Framework for Auxiliary-Loss-Free Load Balancing of Sparse Mixture-of-Experts in Large-Scale AI Models

arXiv:2512.03915v3 Announce Type: replace-cross Abstract: In large-scale AI training, Sparse Mixture-of-Experts (s-MoE) layers enable scaling by activating only a small subset of experts per token. An

A Topology fixated Shape Gradient Framework for Non Simple Boundary Extraction for CIE Lab color images with Repulsive Energy

arXiv:2604.23167v1 Announce Type: new Abstract: A levelset free but a hybrid image segmentation approach based on a modified version of the piece wise constant shape gradient of an Mumford Shah shape

A Unified Fractional Regularization Framework for Sparse Recovery

arXiv:2604.23184v1 Announce Type: cross Abstract: We propose a unified fractional regularization framework for sparse signal recovery based on the ell_1/ell_p^q model. Our main theoretical contributio

A US judge denied Sam Bankman-Fried's request for a new trial based on what SBF called new evidence; SBF tried to withdraw his request, but the judge refused (Bob Van Voris/Bloomberg)

Bob Van Voris / Bloomberg: A US judge denied Sam Bankman-Fried's request for a new trial based on what SBF called new evidence; SBF tried to withdraw his request, but the judge refused — A federal jud

industrytechmeme

A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees

arXiv:2604.24043v1 Announce Type: new Abstract: Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain e

Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter

arXiv:2510.23215v2 Announce Type: replace-cross Abstract: Eigenvalue problems are among the most important topics in many scientific disciplines. With the recent surge and development of machine learn

Accelerating Frequency Domain Diffusion Models with Error-Feedback Event-Driven Caching

arXiv:2604.22901v1 Announce Type: new Abstract: Diffusion models achieve remarkable success in time series generation. However, slow inference limits their practical deployment. We propose E^2-CRF (Er

Accelerating New Product Introduction for Visual Quality Inspection via Few-Shot Diffusion-Based Defect Synthesis

arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int

Accelerating Quantum Materials Characterization: Hybrid Active Learning for Autonomous Spin Wave Spectroscopy

model-releasesarxiv-cs-lg

arXiv:2604.23821v1 Announce Type: cross Abstract: Autonomous neutron spectroscopy must solve three distinct tasks: detection (where is the signal?), inference (which Hamiltonian governs it?), and refi

Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations

arXiv:2604.22794v1 Announce Type: cross Abstract: Reinforcement learning (RL) offers a promising approach for adaptive wind farm flow control, yet its practical deployment is hindered by slow training

agentsarxiv-cs-lg

ACL ARR March 2026 Cycle [D]

researchr-machinelearning

The ACL Rolling Review (ARR) operates on a two-monthly review cycle , and the March 2026 cycle refers to one of these periodic submission and peer review rounds for computational linguistics research.

Active Inference: A method for Phenotyping Agency in AI systems?

arXiv:2604.23278v1 Announce Type: new Abstract: The proliferation of agentic artificial intelligence has outpaced the conceptual tools needed to characterize agency in computational systems. Prevailin

agentsarxiv-cs-ai

Actually Smart Summon now reacts a lot faster

Actually Smart Summon now reacts a lot faster I. Love. Smart Summons. I am going to use it as much as I can now. It truly is usable. Here are some examples. Go test it out. I think you will be very im

industryelon-musk--x

AD-Relight: Training-Free Banner Relighting via Illumination Translation with Diffusion Priors

arXiv:2604.24407v1 Announce Type: new Abstract: The recent surge in content consumption through streaming services has driven a growing demand for personalized content. Personalized advertisements (ad

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models

arXiv:2409.01579v2 Announce Type: replace-cross Abstract: Retrieved documents containing noise will hinder RAG from detecting answer clues and make the inference process slow and expensive. Therefore,

Applications

AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting

arXiv:2604.23239v1 Announce Type: new Abstract: Accurate long-term time series forecasting (LTSF) requires the capture of complex long-range dependencies and dynamic periodic patterns. Recent advances

applicationsarxiv-cs-ai

AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models

arXiv:2604.24175v1 Announce Type: cross Abstract: Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle tempor

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework

model-releasesarxiv-cs-lg

arXiv:2604.23999v1 Announce Type: cross Abstract: Randomized neural networks (RaNNs) are attractive for partial differential equations (PDEs) because they replace expensive end-to-end training with a

Adaptive Multi-Subspace Representation Steering for Attribute Alignment in Large Language Models

arXiv:2508.10599v4 Announce Type: replace Abstract: Activation steering offers a promising approach to controlling the behavior of Large Language Models by directly manipulating their internal activat

Adaptive ToR: Complexity-Aware Tree-Based Retrieval for Pareto-Optimal Multi-Intent NLU

arXiv:2604.24219v1 Announce Type: new Abstract: Multi-intent natural language understanding requires retrieval systems that simultaneously achieve high accuracy and computational efficiency, yet exist

Tools

Adaptive Ultrasound Imaging with Physics-Informed NV-Raw2Insights-US AI

This entry describes NVIDIA's NV-Raw2Insights-US AI model, which uses physics-informed machine learning to enhance ultrasound imaging by adaptively processing raw ultrasound data. The system applies d

toolshugging-face

AdaRubric: Task-Adaptive Rubrics for LLM Agent Evaluation

arXiv:2603.21362v2 Announce Type: replace Abstract: LLM-as-Judge evaluation fails agent tasks because a fixed rubric cannot capture what matters for this task: code debugging demands Correctness and E

Added native metric logging + @TrackioApp integration to ml intern so that you can follow every training run it kicks off in real time. Try …

Added native metric logging + @TrackioApp integration to ml intern so that you can follow every training run it kicks off in real time. Try it by asking 'train a tiny model on a tiny dataset, find som

industryclem-delangue--x

Additive Control Variates Dominate Self-Normalisation in Off-Policy Evaluation

arXiv:2602.14914v2 Announce Type: replace Abstract: Off-policy evaluation (OPE) is essential for assessing ranking and recommendation systems without costly online interventions. Self-Normalised Inver

safetyarxiv-cs-lg

Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance

arXiv:2604.24474v1 Announce Type: new Abstract: Molecular similarity plays a central role in ligand-based drug discovery, such as virtual screening, analog searching, and goal-directed molecular gener