All entries

Enterprises are learning that the assumptions that powered the cloud era are no longer enough

The agentic AI era is forcing a fundamental redesign of enterprise infrastructure — not just in the cloud, but all the way to the on-premises data center. Regulated industries, governments and enterpr

agentssiliconangle

Applications

Enterprises are leaving major AI customer experience gains on the table

DGX agent

Enterprises are investing heavily in AI customer experience, but many experiments are stalling out before ever going live. The culprit is a confidence gap, according to Chris Mina (pictured), chief pr

applicationssiliconangle

23 Apr 2026

Environmental Understanding Vision-Language Model for Embodied Agent

arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a

Epistemic Constitutionalism Or: how to avoid coherence bias

arXiv:2601.14295v3 Announce Type: replace Abstract: Large language models increasingly function as artificial reasoners: they evaluate arguments, assign credibility, and express confidence. Yet their

Epistemology gives a Future to Complementarity in Human-AI Interactions

arXiv:2601.09871v2 Announce Type: replace Abstract: Human-AI complementarity is the claim that a human supported by an AI system can outperform either alone in a decision-making process. Since its int

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

ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation

arXiv:2604.20295v1 Announce Type: new Abstract: Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies t

safetyarxiv-cs-ro

Evals ~= Environments…they’re one of the best investments a team can make for improving agents Step 0: Turn On Tracing for Agents Step 1: Po…

Evals ~= Environments…they’re one of the best investments a team can make for improving agents Step 0: Turn On Tracing for Agents Step 1: Point compute at Traces to understand agent behavior, segment

agentsharrison-chase--x

Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis

arXiv:2604.20577v1 Announce Type: cross Abstract: An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence

Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations

arXiv:2603.15867v2 Announce Type: replace Abstract: The growing use of Machine Learning (ML) tools comes with critical challenges, such as limited model explainability. We propose a global explainabil

Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models

arXiv:2508.17761v3 Announce Type: replace Abstract: In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonl

Eventually LIL Regret: Almost Sure lnln T Regret for a sub-Gaussian Mixture on Unbounded Data

arXiv:2512.12325v3 Announce Type: replace Abstract: We prove that a classic sub-Gaussian mixture proposed by Robbins in a stochastic setting actually satisfies a path-wise (deterministic) regret bound

researcharxiv-cs-lg

Hardware

Every conversation I have with @dylan522p, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in…

Every conversation I have with @dylan522p, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of

hardwaredylan-patel--x

Evian: Towards Explainable Visual Instruction-tuning Data Auditing

arXiv:2604.20544v1 Announce Type: cross Abstract: The efficacy of Large Vision-Language Models (LVLMs) is critically dependent on the quality of their training data, requiring a precise balance betwee

Evidence of Layered Positional and Directional Constraints in the Voynich Manuscript: Implications for Cipher-Like Structure

model-releasesarxiv-cs-cl

arXiv:2604.19762v1 Announce Type: new Abstract: The Voynich Manuscript (VMS) exhibits a script of uncertain origin whose grapheme sequences have resisted linguistic analysis. We present a systematic a

EvoAgent: An Evolvable Agent Framework with Skill Learning and Multi-Agent Delegation

arXiv:2604.20133v1 Announce Type: new Abstract: This paper proposes EvoAgent - an evolvable large language model (LLM) agent framework that integrates structured skill learning with a hierarchical sub

agentsarxiv-cs-ai

EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs

arXiv:2604.19761v1 Announce Type: new Abstract: Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly

EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies

arXiv:2509.03335v3 Announce Type: replace Abstract: In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design

agentsarxiv-cs-lg

Excretion Detection in Pigsties Using Convolutional and Transformerbased Deep Neural Networks

arXiv:2412.00256v3 Announce Type: replace Abstract: Animal excretions in form of urine puddles and feces are a significant source of emissions in livestock farming. Automated detection of soiled floor

researcharxiv-cs-cv

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts

arXiv:2604.19835v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become the dominant architecture for scaling large language models: frontier models routinely decouple total parameters f

Applications

Explainability in Generative Medical Diffusion Models: A Faithfulness-Based Analysis on MRI Synthesis

arXiv:2602.09781v2 Announce Type: replace-cross Abstract: This study investigates the explainability of generative diffusion models in the context of medical imaging, focusing on Magnetic resonance im

applicationsarxiv-cs-ai

Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks

arXiv:2604.19755v1 Announce Type: new Abstract: Anti-money laundering (AML) transaction monitoring generates large volumes of alerts that must be rapidly triaged by investigators under strict audit an

Explainable Speech Emotion Recognition: Weighted Attribute Fairness to Model Demographic Contributions to Social Bias

arXiv:2604.19763v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) systems have growing applications in sensitive domains such as mental health and education, where biased predictions

Explicit Dropout: Deterministic Regularization for Transformer Architectures

arXiv:2604.20505v1 Announce Type: new Abstract: Dropout is a widely used regularization technique in deep learning, but its effects are typically realized through stochastic masking rather than explic

researcharxiv-cs-lg

Exploiting LLM-as-a-Judge Disposition on Free Text Legal QA via Prompt Optimization

arXiv:2604.20726v1 Announce Type: cross Abstract: This work explores the role of prompt design and judge selection in LLM-as-a-Judge evaluations of free text legal question answering. We examine wheth

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom

arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories p

Tutorials

Exploring High-Order Self-Similarity for Video Understanding

arXiv:2604.20760v1 Announce Type: new Abstract: Space-time self-similarity (STSS), which captures visual correspondences across frames, provides an effective way to represent temporal dynamics for vid

tutorialsarxiv-cs-cv

Exploring Spatial Intelligence from a Generative Perspective

model-releasesarxiv-cs-cv

arXiv:2604.20570v1 Announce Type: new Abstract: Spatial intelligence is essential for multimodal large language models, yet current benchmarks largely assess it only from an understanding perspective.

Extract PDF text in your browser with LiteParse for the web

model-releasessimon-willison

LlamaIndex have a most excellent open source project called LiteParse, which provides a Node.js CLI tool for extracting text from PDFs. I got a version of LiteParse working entirely in the browser, us

Local Ai

FA-Seg: A Fast and Accurate Diffusion-Based Method for Open-Vocabulary Segmentation

arXiv:2506.23323v5 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Al

local-aiarxiv-cs-cv

Fairness-Aware Multi-Group Target Detection in Online Discussion

arXiv:2407.11933v4 Announce Type: replace Abstract: Target-group detection is the task of detecting which group(s) a piece of content is ``directed at or about''. Applications include targeted marketi

Fairness Testing of Large Language Models in Role-Playing

arXiv:2411.00585v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A cr

Falcon 9 launches 24 @Starlink satellites from California

model-releaseselon-musk--x

SpaceX's Falcon 9 rocket successfully launched 24 Starlink satellites from a California launch facility, continuing the company's ongoing deployment of its satellite internet constellation. This missi

Fast Amortized Fitting of Scientific Signals Across Time and Ensembles via Transferable Neural Fields

arXiv:2604.19979v1 Announce Type: cross Abstract: Neural fields, also known as implicit neural representations (INRs), offer a powerful framework for modeling continuous geometry, but their effectiven

researcharxiv-cs-cv

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

arXiv:2604.20735v1 Announce Type: new Abstract: Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertain

Fast-then-Fine: A Two-Stage Framework with Multi-Granular Representation for Cross-Modal Retrieval in Remote Sensing

model-releasesarxiv-cs-cv

arXiv:2604.20429v1 Announce Type: new Abstract: Remote sensing (RS) image-text retrieval plays a critical role in understanding massive RS imagery. However, the dense multi-object distribution and com

Faster Fixed-Point Methods for Multichain MDPs

arXiv:2506.20910v2 Announce Type: replace-cross Abstract: We study value-iteration (VI) algorithms for solving general (a.k.a. multichain) Markov decision processes (MDPs) under the average-reward cri

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation

arXiv:2506.21095v4 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative training while preserving privacy, yet it introduces a critical challenge: the 'illusion of fair

Applications

Federated Learning over Blockchain-Enabled Cloud Infrastructure

arXiv:2604.20062v1 Announce Type: new Abstract: The rise of IoT devices and the uptake of cloud computing have informed a new era of data-driven intelligence. Traditional centralized machine learning

applicationsarxiv-cs-lg

FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels

arXiv:2604.20825v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed client

researcharxiv-cs-ai

FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data

arXiv:2510.25223v3 Announce Type: replace Abstract: Event log data, recording fine-grained user actions and system events, represent one of the most valuable assets for modern digital services. Howeve

agentsarxiv-cs-ai

Industry

Feminization of the West creates the fertile landscape for suicidal empathy.

I can't verify the specific content of this post, as the URL appears invalid (X post IDs don't match that format). The title suggests a post making claims about cultural feminization and its alleged s

industryelon-musk--x

Fextsuperscript{2}LP-AP: Fast & Flexible Label Propagation with Adaptive Propagation Kernel

arXiv:2604.20736v1 Announce Type: new Abstract: Semi-supervised node classification is a foundational task in graph machine learning, yet state-of-the-art Graph Neural Networks (GNNs) are hindered by

Industry

Filing: Netflix plans a 25B share buyback, adding to a Dec. 2024 program that still has 6.8B for purchases; NFLX is down 13% since its Q1 earnings on April 16 (Amy Thomson/Bloomberg)

Amy Thomson / Bloomberg: Filing: Netflix plans a 25B share buyback, adding to a Dec. 2024 program that still has 6.8B for purchases; NFLX is down 13% since its Q1 earnings on April 16 — Netflix Inc. p

industrytechmeme

Finding Duplicates in 1.1M BDD Steps: cukereuse, a Paraphrase-Robust Static Detector for Cucumber and Gherkin

model-releasesarxiv-cs-cl

arXiv:2604.20462v1 Announce Type: cross Abstract: Behaviour-Driven Development (BDD) suites accumulate step-text duplication whose maintenance cost is established in prior work. Existing detection tec

FingerEye: Continuous and Unified Vision-Tactile Sensing for Dexterous Manipulation

arXiv:2604.20689v1 Announce Type: new Abstract: Dexterous robotic manipulation requires comprehensive perception across all phases of interaction: pre-contact, contact initiation, and post-contact. Su

safetyarxiv-cs-ro

First time fine-tuning, need a sanity check — 3B or 7B for multi-task reasoning? [D]

researchr-machinelearning

This Reddit discussion post addresses a beginner's question about choosing between 3B and 7B parameter models for fine-tuning on multi-task reasoning problems. The post likely contains advice from exp

FlashNorm: Fast Normalization for Transformers

arXiv:2407.09577v4 Announce Type: replace Abstract: Normalization layers are ubiquitous in large language models (LLMs) yet represent a compute bottleneck: on hardware with distinct vector and matrix