Search: “framework”

Interventional Time Series Priors for Causal Foundation Models

arXiv:2603.11090v2 Announce Type: replace Abstract: Prior-data fitted networks (PFNs) have emerged as powerful foundation models for tabular causal inference, yet their extension to time series remain

researcharxiv-cs-lg

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KEO: Knowledge Extraction on OMIn via Knowledge Graphs and RAG for Safety-Critical Aviation Maintenance

DGX agent

arXiv:2510.05524v2 Announce Type: replace Abstract: We present Knowledge Extraction on OMIn (KEO), a domain-specific knowledge extraction and reasoning framework with large language models (LLMs) in s

model-releasesarxiv-cs-cl

10 Apr 2026

LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents

arXiv:2512.17445v2 Announce Type: replace Abstract: LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represe

safetyarxiv-cs-cv

Learning Without Losing Identity: Capability Evolution for Embodied Agents

arXiv:2604.07799v1 Announce Type: new Abstract: Embodied agents are expected to operate persistently in dynamic physical environments, continuously acquiring new capabilities over time. Existing appro

safetyarxiv-cs-ro

Lighting-grounded Video Generation with Renderer-based Agent Reasoning

arXiv:2604.07966v1 Announce Type: new Abstract: Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as

agentsarxiv-cs-cv

Applications

LLM-Based Data Generation and Clinical Skills Evaluation for Low-Resource French OSCEs

arXiv:2604.08126v1 Announce Type: new Abstract: Objective Structured Clinical Examinations (OSCEs) are the standard method for assessing medical students' clinical and communication skills through str

applicationsarxiv-cs-cl

LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization

arXiv:2510.13907v3 Announce Type: replace Abstract: Large language models (LLMs) are highly sensitive to prompts, but most automatic prompt optimization (APO) methods assume access to ground-truth ref

researcharxiv-cs-cl

Industry

Memory Scaling for AI Agents

Databricks Research introduced **MemAlign**, a memory framework for AI agents that stores past interactions as episodic memories and uses an LLM to distill them into generalized semantic rules, whi...

industrydatabricks

Applications

Mitigating Domain Drift in Multi Species Segmentation with DINOv2: A Cross-Domain Evaluation in Herbicide Research Trials

arXiv:2508.07514v3 Announce Type: replace Abstract: Reliable plant species and damage segmentation for herbicide field research trials requires models that can withstand substantial real-world variati

applicationsarxiv-cs-cv

mlx @ollama!

Ollama released a preview version (0.19) on March 31, 2026, built on top of Apple's open-source MLX framework, enabling local LLMs to run significantly faster on Apple Silicon Macs by leveraging th...

model-releasesollama--x

More Capable, Less Cooperative? When LLMs Fail At Zero-Cost Collaboration

arXiv:2604.07821v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly coordinate in multi-agent systems, yet we lack an understanding of where and why cooperation failures m

agentsarxiv-cs-cl

Negotiating Privacy with Smart Voice Assistants: Risk-Benefit and Control-Acceptance Tensions

arXiv:2604.06235v1 Announce Type: cross Abstract: Smart Voice assistants (SVAs) are widely adopted by youth, yet privacy decision-making in these environments is often characterized by competing consi

researcharxiv-cs-ai

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

arXiv:2510.12088v2 Announce Type: replace Abstract: Symbolic world modeling requires inferring and representing an environment's transitional dynamics as an executable program. Prior work has focused

agentsarxiv-cs-ai

OpenTrack3D: Towards Accurate and Generalizable Open-Vocabulary 3D Instance Segmentation

arXiv:2512.03532v2 Announce Type: replace Abstract: Generalizing open-vocabulary 3D instance segmentation (OV-3DIS) to diverse, unstructured, and mesh-free environments is crucial for robotics and AR/

Preventing Overfitting in Deep Image Prior for Hyperspectral Image Denoising

arXiv:2604.08272v1 Announce Type: new Abstract: Deep image prior (DIP) is an unsupervised deep learning framework that has been successfully applied to a variety of inverse imaging problems. However,

PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation

model-releasesarxiv-cs-cv

arXiv:2604.08037v1 Announce Type: cross Abstract: Talking-head generation has advanced rapidly with diffusion-based generative models, but training usually depends on centralized face-video and speech

Pseudo-Expert Regularized Offline RL for End-to-End Autonomous Driving in Photorealistic Closed-Loop Environments

arXiv:2512.18662v2 Announce Type: replace-cross Abstract: End-to-end (E2E) autonomous driving models that take only camera images as input and directly predict a future trajectory are appealing for th

agentsarxiv-cs-cv

Local Ai

Quantifying Explanation Consistency: The C-Score Metric for CAM-Based Explainability in Medical Image Classification

arXiv:2604.08502v1 Announce Type: new Abstract: Class Activation Mapping (CAM) methods are widely used to generate visual explanations for deep learning classifiers in medical imaging. However, existi

local-aiarxiv-cs-cv

Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach

model-releasesarxiv-cs-lg

arXiv:2604.06541v1 Announce Type: cross Abstract: We investigate whether a multiscale tensor-network architecture can provide a useful inductive bias for reconstruction-based anomaly detection in coll

RAGE-XY: RADAR-Aided Longitudinal and Lateral Forces Estimation For Autonomous Race Cars

arXiv:2604.07939v1 Announce Type: new Abstract: In this work, we present RAGE-XY, an extended version of RAGE, a real-time estimation framework that simultaneously infers vehicle velocity, tire slip a

agentsarxiv-cs-ro

Applications

Reasoning-Based Refinement of Unsupervised Text Clusters with LLMs

arXiv:2604.07562v1 Announce Type: new Abstract: Unsupervised methods are widely used to induce latent semantic structure from large text collections, yet their outputs often contain incoherent, redund

applicationsarxiv-cs-cl

Local Ai

Region-Graph Optimal Transport Routing for Mixture-of-Experts Whole-Slide Image Classification

arXiv:2604.07298v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) is the dominant framework for gigapixel whole-slide image (WSI) classification in computational pathology. However, c

local-aiarxiv-cs-ai

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs

arXiv:2604.07765v1 Announce Type: new Abstract: Earth Observation (EO) systems are essentially designed to support domain experts who often express their requirements through vague natural language ra

agentsarxiv-cs-cv

RewardFlow: Generate Images by Optimizing What You Reward

arXiv:2604.08536v1 Announce Type: new Abstract: We introduce RewardFlow, an inversion-free framework that steers pretrained diffusion and flow-matching models at inference time through multi-reward La

safetyarxiv-cs-cv

Hardware

RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs

arXiv:2510.19225v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows i

hardwarearxiv-cs-lg

Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding

model-releasesarxiv-cs-cl

arXiv:2604.07753v1 Announce Type: cross Abstract: Empowering Large Multimodal Models (LMMs) with image generation often leads to catastrophic forgetting in understanding tasks due to severe gradient c

Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation

arXiv:2604.07916v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) aims to segment image regions described by natural-language expressions, serving as a bridge between vision and

TEMPER: Testing Emotional Perturbation in Quantitative Reasoning

model-releasesarxiv-cs-cl

arXiv:2604.07801v1 Announce Type: new Abstract: Large language models are trained and evaluated on quantitative reasoning tasks written in clean, emotionally neutral language. However, real-world quer

The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours

model-releasesarxiv-cs-lg

arXiv:2604.07267v1 Announce Type: cross Abstract: Gaussian process (GP) regression is a widely used non-parametric modeling tool, but its cubic complexity in the training size limits its use on mass

Unifying Speech Editing Detection and Content Localization via Prior-Enhanced Audio LLMs

model-releasesarxiv-cs-ai

arXiv:2601.21463v2 Announce Type: replace-cross Abstract: Existing speech editing detection (SED) datasets are predominantly constructed using manual splicing or limited editing operations, resulting

VisCoder2: Building Multi-Language Visualization Coding Agents

model-releasesarxiv-cs-ai

arXiv:2510.23642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently enabled coding agents capable of generating, executing, and revising visualization code. However, e

VSAS-BENCH: Real-Time Evaluation of Visual Streaming Assistant Models

model-releasesarxiv-cs-cv

arXiv:2604.07634v1 Announce Type: new Abstract: Streaming vision-language models (VLMs) continuously generate responses given an instruction prompt and an online stream of input frames. This is a core

What Makes an Ideal Quote? Recommending 'Unexpected yet Rational' Quotations via Novelty

arXiv:2602.22220v2 Announce Type: replace-cross Abstract: Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize sur

safetyarxiv-cs-ai

What’s new with Google Cloud

model-releasesgoogle-cloud-ai

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not

Why Are We Lonely? Leveraging LLMs to Measure and Understand Loneliness in Caregivers and Non-caregivers

model-releasesarxiv-cs-cl

arXiv:2604.07834v1 Announce Type: new Abstract: This paper presents an LLM-driven approach for constructing diverse social media datasets to measure and compare loneliness in the caregiver and non-car

FlowInOne - A new Multimodal image model . Released on Huggingface

model-releasesr-stablediffusion

FlowInOne is a vision-centric multimodal image generation framework that reformulates multimodal generation as a purely visual flow, converting all inputs into visual prompts and enabling a clean i...

9 Apr 2026

Introducing the Child Safety Blueprint

OpenAI's Child Safety Blueprint, released in April 2026, is a policy framework aimed at combating the rise of AI-enabled child sexual exploitation by combining legal, operational, and technical app...

safetyopenai

8 Apr 2026

Hardware

New Vultr Identity and Access Management Upgrades

Vultr has upgraded its Identity and Access Management (IAM) framework by replacing legacy ACLs with fine-grained, policy-driven access controls, enabling organizations to assign roles, manage permi...

hardwarevultr

8 Apr 2026

Using a non-hermetic agent and having trouble with GPT 5.4 or your Codex sub? The rumors are true: it works a lot better with the Hermes spe…

Nous Research's **Hermes Agent** is an open-source agentic framework by NousResearch that delivers significantly improved reliability when using GPT-5.x or Codex (OpenAI Codex subscription) models ...

agentsnous-research--x

8 Apr 2026

A Large-Scale Dataset for Multi-Class Financial News Classification in Brazilian Portuguese

arXiv:2610.20630v1 Announce Type: new Abstract: The development of Financial Natural Language Processing (NLP) systems for Brazilian Portuguese is hindered by the scarcity of domain-specific datasets.

researcharxiv-cs-cl

AI safety worries multiply but everyone’s still racing full speed ahead

The drumbeat over how safe artificial intelligence is — or more to the point, isn’t — just keeps louder. In the wake of weeks of incidents involving rogue agents, with likely more to come, more govern

safetysiliconangle

Hardware

ANEForge: Python for direct computation on the Apple Neural Engine

arXiv:2606.17090v2 Announce Type: replace-cross Abstract: ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device,

hardwarearxiv-cs-ai

Anvil: Scaling Embodied Spatial Intelligence through Knowledge Recirculation

arXiv:2610.21882v1 Announce Type: cross Abstract: Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this kno

researcharxiv-cs-ai

Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines

arXiv:2610.22277v1 Announce Type: cross Abstract: When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while adhering to legal constraints. T

agentsarxiv-cs-ro

AVALON: Zero-Shot Indoor Navigation with Human-Seeded Topological Memory

arXiv:2610.21586v1 Announce Type: cross Abstract: Indoor service robots often enter unmapped buildings whose layouts and task constraints are already familiar to users. We address this human-familiar,

safetyarxiv-cs-ai

Can World and Action Modeling Benefit Each Other under Unified Causal Training?

arXiv:2610.21095v1 Announce Type: new Abstract: World and action modeling are closely related, yet their reciprocal benefits under unified causal training remain unclear. We introduce OneWM, a simple

safetyarxiv-cs-cv

Clinically Interpretable Biological Age Estimation Using CatBoost and SHAP with Continuous and Categorical Features from NHANES

arXiv:2610.20868v1 Announce Type: new Abstract: Biological age (BA) captures inter-individual variation in physiological aging beyond chronological age (CA). Although machine-learning models have adva

researcharxiv-cs-lg

CoDeFont: One-Shot Font Generation via Multi-Scale Factor-Specific Representation Learning

arXiv:2610.21364v1 Announce Type: new Abstract: One-shot Font Generation (OFG) aims to synthesize a target glyph by transferring the stylistic characteristics of a single reference glyph while preserv