Search: “concepts”

ESGLens: An LLM-Based RAG Framework for Interactive ESG Report Analysis and Score Prediction

arXiv:2604.19779v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reports are central to investment decision-making, yet their length, heterogeneous content, and lack of stan

researcharxiv-cs-cl

Local Diffusion Models and Phases of Data Distributions

DGX agent

arXiv:2508.06614v2 Announce Type: replace Abstract: As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance i

tutorialsarxiv-cs-lg

23 Apr 2026

Mechanistic Interpretability Tool for AI Weather Models

arXiv:2604.20467v1 Announce Type: cross Abstract: Artificial Intelligence (AI) weather models are improving rapidly, and their forecasts are already competitive with long-established traditional Numer

Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference

arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on

local-aiarxiv-cs-ro

Representational Alignment Across Model Layers and Brain Regions with Multi-Level Optimal Transport

arXiv:2510.01706v2 Announce Type: replace-cross Abstract: Standard representational similarity methods align each layer of a network to its best match in another independently, producing asymmetric re

safetyarxiv-cs-ai

Tools

Supporting people with a vision who want to build something from the ground up. Join Kamau - creative strategist - in building ideas fast wi…

This post from Replit promotes a workshop or collaboration opportunity led by creative strategist Kamau focused on rapid idea development and building projects from scratch. The initiative targets ind

toolsreplit--x

Surrogate modeling for interpreting black-box LLMs in medical predictions

arXiv:2604.20331v1 Announce Type: cross Abstract: Large language models (LLMs), trained on vast datasets, encode extensive real-world knowledge within their parameters, yet their black-box nature obsc

applicationsarxiv-cs-ai

Taint-Style Vulnerability Detection and Confirmation for Node.js Packages Using LLM Agent Reasoning

arXiv:2604.20179v1 Announce Type: cross Abstract: The rapidly evolving Node.js ecosystem currently includes millions of packages and is a critical part of modern software supply chains, making vulnera

To Know is to Construct: Schema-Constrained Generation for Agent Memory

arXiv:2604.20117v1 Announce Type: new Abstract: Constructivist epistemology argues that knowledge is actively constructed rather than passively copied. Despite the generative nature of Large Language

TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs

arXiv:2604.20043v1 Announce Type: cross Abstract: Explainability for Large Language Model (LLM) agents is especially challenging in interactive, partially observable settings, where decisions depend o

agentsarxiv-cs-ai

Where are they looking in the operating room?

arXiv:2604.20574v1 Announce Type: new Abstract: Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studied in computer vision, advancing research in visual a

researcharxiv-cs-cv

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization

arXiv:2604.08404v2 Announce Type: replace Abstract: Out-of-distribution (OoD) generalization occurs when representation learning encounters a distribution shift. This occurs frequently in practice whe

Characterizing AlphaEarth Embedding Geometry for Agentic Environmental Reasoning

arXiv:2604.18715v1 Announce Type: cross Abstract: Earth observation foundation models encode land surface information into dense embedding vectors, yet the geometric structure of these representations

Enabling Vibration-Based Gesture Recognition on Everyday Furniture via Energy-Efficient FPGA Implementation of 1D Convolutional Networks

arXiv:2510.23156v2 Announce Type: replace-cross Abstract: The growing demand for smart home interfaces has increased interest in non-intrusive sensing methods like vibration-based gesture recognition.

applicationsarxiv-cs-ai

Epistemic Skills: Reasoning about Knowledge and Oblivion

arXiv:2504.01733v4 Announce Type: replace Abstract: This paper presents a class of epistemic logics that captures the dynamics of acquiring knowledge and descending into oblivion, while incorporating

researcharxiv-cs-ai

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

Go from Blockout to Final Render with Seedance 2.0 https://x.com/i/broadcasts/1MKgNgykZRlxL

Seedance 2.0 is a ComfyUI tool or workflow that enables users to progress from initial blockout stages through to final rendered output in a streamlined process. The broadcast likely demonstrates the

local-aicomfyui--x

Has Automated Essay Scoring Reached Sufficient Accuracy? Deriving Achievable QWK Ceilings from Classical Test Theory

arXiv:2604.19131v1 Announce Type: new Abstract: Automated essay scoring (AES) is commonly evaluated on public benchmarks using quadratic weighted kappa (QWK). However, because benchmark labels are ass

Introducing Gemini Enterprise Agent Platform, powering the next wave of agents

model-releasesgoogle-cloud-ai

In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control

arXiv:2604.19018v1 Announce Type: cross Abstract: Inference-time LLM alignment methods, particularly activation steering, offer an alternative to fine-tuning by directly modifying activations during g

local-aiarxiv-cs-ai

Multi-modal Reasoning with LLMs for Visual Semantic Arithmetic

arXiv:2604.19567v1 Announce Type: new Abstract: Reinforcement learning (RL) as post-training is crucial for enhancing the reasoning ability of large language models (LLMs) in coding and math. However,

safetyarxiv-cs-ai

Next '26 Hands-On: 10 Codelabs to Build Featured Tech

Significant contributors to this article include Megan O'Keefe, Senior Staff Developer Advocate, and Karl Weinmeister, Director of Developer Relations. Whether you are joining us in person in Las Vega

agentsgoogle-cloud-ai

Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

local-aiarxiv-cs-ai

Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability

arXiv:2604.18893v1 Announce Type: cross Abstract: A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including

safetyarxiv-cs-ai

Small and midsize businesses jumpstart their AI transformations with Gemini Enterprise

model-releasesgoogle-cloud-ai

Small businesses are the backbone of the global economy. With 400 million SMBs worldwide and 36 million in the U.S. alone, they provide 50% of global employment. Now, with Google Cloud AI, they’re sca

What’s next in Google AI infrastructure: Scaling for the agentic era

model-releasesgoogle-cloud-ai

AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

arXiv:2604.18570v1 Announce Type: cross Abstract: Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin

applicationsarxiv-cs-cl

Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration

arXiv:2508.18025v4 Announce Type: replace-cross Abstract: Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive comp

agentsarxiv-cs-cv

Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2604.17388v1 Announce Type: new Abstract: We introduce JuRe (Just Repair), a minimal denoising network for time series anomaly detection that exposes a central finding: architectural complexity

Tutorials

Block-encodings as programming abstractions: The Eclipse Qrisp BlockEncoding Interface

arXiv:2604.18276v1 Announce Type: cross Abstract: Block-encoding is a foundational technique in modern quantum algorithms, enabling the implementation of non-unitary operations by embedding them into

tutorialsarxiv-cs-lg

ComPASS: Towards Personalized Agentic Social Support via Tool-Augmented Companionship

arXiv:2604.18356v1 Announce Type: new Abstract: Developing compassionate interactive systems requires agents to not only understand user emotions but also provide diverse, substantive support. While r

Creating ConLangs to Probe the Metalinguistic Grammatical Knowledge of LLMs

arXiv:2510.07591v3 Announce Type: replace Abstract: We present a system that uses LLMs as a tool in the development of Constructed Languages -- ConLangs, which we call IASC (Interactive Agentic System

Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis

arXiv:2604.16459v1 Announce Type: cross Abstract: Fault intensity diagnosis (FID) plays a pivotal role in intelligent manufacturing while neglecting dependencies among target classes hinders its pract

applicationsarxiv-cs-cv

Industry

Democrats in Virginia today are voting to strip democracy from the process, eliminating Republican voices from congress They are fascists an…

Democrats in Virginia today are voting to strip democracy from the process, eliminating Republican voices from congress They are fascists and unrepentant The actions of Texas or any other state are im

industryelon-musk--x

Enhancing classification accuracy through chaos

arXiv:2603.15299v2 Announce Type: replace Abstract: We propose a novel approach which exploits chaos to enhance classification accuracy. Specifically, the available data that need to be classified are

Fast Online 3D Multi-Camera Multi-Object Tracking and Pose Estimation

arXiv:2604.16522v1 Announce Type: new Abstract: This paper proposes a fast and online method for jointly performing 3D multi-object tracking and pose estimation using multiple monocular cameras. Our a

researcharxiv-cs-cv

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD

arXiv:2604.18491v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is central to race-car aerodynamic development, yet its cost -- tens of thousands of core-hours per high-fidelity eva

From Clinical Intent to Clinical Model: An Autonomous Coding-Agent Framework for Clinician-driven AI Development

arXiv:2604.17110v1 Announce Type: new Abstract: Clinical AI development has traditionally followed a collaborative paradigm that depends on close interaction between clinicians and specialized AI team

agentsarxiv-cs-cv

Tutorials

Graph neural network for colliding particles with an application to sea ice floe modeling

arXiv:2602.16213v2 Announce Type: replace-cross Abstract: This paper introduces a novel approach to sea ice modeling using Graph Neural Networks (GNNs), utilizing the natural graph structure of sea ic

tutorialsarxiv-cs-cv

Injecting Structured Biomedical Knowledge into Language Models: Continual Pretraining vs. GraphRAG

arXiv:2604.16422v1 Announce Type: new Abstract: The injection of domain-specific knowledge is crucial for adapting language models (LMs) to specialized fields such as biomedicine. While most current a

Interdisciplinary Workshop on Mechanical Intelligence: Summary Report

arXiv:2604.16381v1 Announce Type: new Abstract: This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) r

researcharxiv-cs-ro

KIRA: Knowledge-Intensive Image Retrieval and Reasoning Architecture for Specialized Visual Domains

model-releasesarxiv-cs-cv

arXiv:2604.16915v1 Announce Type: new Abstract: Retrieval augmented generation (RAG) has transformed text based question answering, yet its extension to visual domains remains hindered by fundamental

MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation

arXiv:2512.20626v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to dynamically access external information, which is powerful for an

researcharxiv-cs-cl

MESA: A Training-Free Multi-Exemplar Deep Framework for Restoring Ancient Inscription Textures

arXiv:2604.17390v1 Announce Type: new Abstract: Ancient inscriptions frequently suffer missing or corrupted regions from fragmentation, erosion, or other damage, hindering reading, and analysis. We re

safetyarxiv-cs-cv

Tutorials

mlr3torch: A Deep Learning Framework in R based on mlr3 and torch

arXiv:2604.18152v1 Announce Type: cross Abstract: Deep learning (DL) has become a cornerstone of modern machine learning (ML) praxis. We introduce the R package mlr3torch, which is an extensible DL fr

tutorialsarxiv-cs-lg

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

arXiv:2604.16518v1 Announce Type: new Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit percepti

safetyarxiv-cs-ro

Rate-Distortion Optimization for Transformer Inference

arXiv:2601.22002v3 Announce Type: replace Abstract: Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be ma

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction

arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In

safetyarxiv-cs-lg