Search: “index”

RoboPIN: Grounded Embodied Reasoning via Pinned Chain-of-Thought

arXiv:2606.15753v2 Announce Type: replace Abstract: Embodied reasoning requires models to perceive task-relevant objects and spaces in physical environments and maintain consistent visual grounding th

safetyarxiv-cs-ai

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Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics

DGX agent

arXiv:2606.28387v1 Announce Type: cross Abstract: Enterprise text-to-SQL systems often fail before SQL is generated: the model receives the wrong schema context. Modern warehouses contain thousands of

applicationsarxiv-cs-ai

30 Jun 2026

SciIR: A Large-scale Training Dataset and Benchmark for Scientific Image Reasoning Generation

model-releasesarxiv-cs-cv

arXiv:2606.30124v1 Announce Type: new Abstract: While Text-to-Image (T2I) models have shown remarkable success in generating photorealistic visual content, they still struggle with the rigorous semant

Self-Evolving Agentic Image Restoration via Deliberate Planning and Intuitive Execution

arXiv:2606.28971v1 Announce Type: new Abstract: Real-world image restoration (IR) remains challenging due to complex and coupled degradations. While recent agentic IR frameworks leverage Large Languag

agentsarxiv-cs-cv

t-STEP: An interpretable model for Total Electron Content predictions and irregularities estimations

arXiv:2606.29644v1 Announce Type: new Abstract: Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheri

The Joint Effect of Quantization and Sampling Temperature on LLM Safety Alignment: A Factorial Analysis

arXiv:2606.29581v1 Announce Type: cross Abstract: Modern LLM deployments routinely compress models and raise sampling temperature to reduce cost, latency, or repetition, yet safety evaluations usually

safetyarxiv-cs-ai

Tumor-aware augmentation with task-guided attention analysis improves rectal cancer segmentation from magnetic resonance images

model-releasesarxiv-cs-cv

arXiv:2605.05522v2 Announce Type: replace-cross Abstract: Although self-supervised pretraining is expected to learn broadly transferable representations, its effectiveness across imaging modalities su

Curriculum-guided Change Detection Training: Toward Accurate Serac Fall Monitoring

model-releasesarxiv-cs-cv

arXiv:2606.28012v1 Announce Type: new Abstract: Change Detection (CD) aims to identify semantic or structural changes from nearly registered multi-temporal images. While recent advances in training me

29 Jun 2026

Multimodal Evaluator Preference Collapse: Cross-Modal Coupling in Self-Evolving Agents

model-releasesarxiv-cs-cl

arXiv:2606.16682v3 Announce Type: replace-cross Abstract: When AI agents use language models to evaluate their own outputs in a feedback loop, systematic biases emerge. We show that Evaluator Preferen

29 Jun 2026

The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails

arXiv:2606.27462v1 Announce Type: cross Abstract: The global minimum-variance portfolio (GMVP) is the canonical decision built from an estimated covariance matrix, yet covariance estimators are univer

29 Jun 2026

A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI

arXiv:2606.26718v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models u

researcharxiv-cs-ai

Beyond Global Divergences: A Local-Mass Perspective on Bayesian Inference

arXiv:2606.27090v1 Announce Type: cross Abstract: Global objectives, such as KL divergence and ELBO, are widely used in Bayesian inference for measuring distributional discrepancy. This paper studies

Boundary-Aware Context Grounding for A Low-Channel EEG Agent

arXiv:2606.26519v1 Announce Type: new Abstract: Large language models (LLMs) can make scientific software easier to use. However, a general model does not automatically know which measurements a parti

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting

arXiv:2510.20769v2 Announce Type: replace-cross Abstract: Accurate medium-range precipitation forecasting is essential for hydrometeorological risk management but remains challenging for both numerica

safetyarxiv-cs-lg

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents

arXiv:2606.26122v1 Announce Type: new Abstract: Recent methods train search agents via reinforcement learning from (question, answer, evidence) tuples without requiring expert trajectories. The tuples

safetyarxiv-cs-cv

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

arXiv:2606.27277v1 Announce Type: new Abstract: Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. I

Applications

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

arXiv:2506.15681v4 Announce Type: replace Abstract: Recent advancements in vision-language models (VLMs) have leveraged large language models (LLMs) to achieve performance on par with closed-source sy

applicationsarxiv-cs-cl

Geometric Fairness-Aware Routing for Federated Edge Networks

arXiv:2606.26125v1 Announce Type: cross Abstract: Emerging 6G and edge-intelligent networks require effective and balanced routing algorithms among varied and spatially distributed devices. Existing f

safetyarxiv-cs-ai

Industry

How Databricks is turning video into searchable, actionable intelligence

Databricks describes how its platform enables organizations to process and analyze video data, converting raw video content into searchable and actionable intelligence through machine learning and dat

industrydatabricks

LogicIR: Logic Gate Networks for Image Restoration

arXiv:2606.26609v1 Announce Type: new Abstract: Image restoration aims to reconstruct high-quality images from degraded low-quality inputs. As the computational demands of image restoration models con

Memory Depth, Not Memory Access: Selective Parametric Consolidation for Long-Running Language Agents

arXiv:2606.26806v1 Announce Type: new Abstract: Long-running language agents need more than memory access. Retrieval systems can fetch past facts at query time, but they do not decide which experience

Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariates

arXiv:2602.17683v3 Announce Type: replace-cross Abstract: Short-term forecasting of vegetation dynamics is a key enabler for data-driven decision support in precision agriculture. Normalized Differenc

ProvenAI: Provenance-Native Traces of Evidence in Generated Answers

arXiv:2606.26449v1 Announce Type: cross Abstract: Retrieval-augmented systems routinely present citations alongside generated answers, yet a citation does not confirm that the corresponding source mea

TaskTok: Delving into Task Tokens for Task-driven Image Restoration

arXiv:2606.26615v1 Announce Type: new Abstract: While traditional image restoration focuses on perceptual quality, Task-Driven Image Restoration (TDIR) aims to maximize the performance of downstream h

The @n8n_io node for the LlamaParse Platform is now an officially verified community node🦙 Out of the box, you get access to parsing, split…

The @n8n_io node for the LlamaParse Platform is now an officially verified community node🦙 Out of the box, you get access to parsing, splitting, classification, structured data extraction and retrieva

agentsjerry-liu--x

You can now equip your n8n workflows with the world's best parsing/extraction over your most complex documents 📃💫 We're excited to announc…

You can now equip your n8n workflows with the world's best parsing/extraction over your most complex documents 📃💫 We're excited to announce that LlamaParse is now an officially verified community node

agentsjerry-liu--x

BitNet Text Embeddings

arXiv:2606.25674v1 Announce Type: new Abstract: LLM-based text embedders have substantially improved retrieval and semantic representation quality, but their deployment remains costly: large backbone

researcharxiv-cs-cl

Cross-Attention Multimodal Learning for Predicting Response to Neoadjuvant Imatinib in Gastrointestinal Stromal Tumors: A Multicenter Retrospective Study

arXiv:2606.25579v1 Announce Type: cross Abstract: Background: Response to neoadjuvant imatinib in gastrointestinal stromal tumors (GISTs) is highly variable and cannot be reliably predicted using curr

Failure Modes of Large Language Models on Research-Level Mathematics: A Taxonomy and an Empirical Characterisation

arXiv:2606.24902v1 Announce Type: cross Abstract: The 'First Proof' benchmark [1] posed ten research-level mathematics questions to the strongest publicly available LLMs and found them consistently wr

How Robust is OCR-Reasoning? Evaluating OCR-Reasoning Robustness of Vision-Language Models under Visual Perturbations

model-releasesarxiv-cs-cl

arXiv:2606.26041v1 Announce Type: cross Abstract: Vision-language models (VLMs) have achieved strong performance on OCR-based benchmarks and increasingly focused on text-rich understanding, but their

Invisible to humans, visible to machines: a preregistered audit of Unicode fidelity across four biomedical bibliographic APIs

arXiv:2606.24897v1 Announce Type: cross Abstract: Biomedical text mining, scientometrics, and the construction of training corpora for biomedical large language models (LLMs) all assume that the abstr

researcharxiv-cs-cl

Learning Asynchronous Upper-body Task-space Trajectory Tracking Policy for Humanoid Robots

arXiv:2606.25706v1 Announce Type: new Abstract: High-level humanoid planners often output sparse task-space, low-rate trajectories, whereas whole-body controllers run at high frequency. This creates t

safetyarxiv-cs-ro

Measurable Majorities Are Not Finitely Axiomatizable

arXiv:2606.25954v1 Announce Type: cross Abstract: This theoretical note studies the finite axiomatizability of strict majority reasoning in finite social decision frames. Moss and Pedersen (2026) intr

researcharxiv-cs-ai

Physics-conforming Latent Twins

arXiv:2606.15053v2 Announce Type: replace Abstract: Surrogate models are central to scientific machine learning, where they enable fast prediction, simulation, inference, and control for complex physi

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems

arXiv:2606.25533v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retri

local-aiarxiv-cs-cl

Story Operators: Decomposing the Original o Sequel Transformation in Embedding Space

model-releasesarxiv-cs-cl

arXiv:2606.25379v1 Announce Type: new Abstract: I treat a book as a point in a sentence-embedding space and a literary transformation as an operation on points. Given an original novel and its sequel,

DramaDirector: Geometry-Guided Short Drama Generation

arXiv:2606.24107v1 Announce Type: cross Abstract: Short dramas, with their rapid shot rhythms, dialogue-driven focus shifts, and demanding cinematographic grounding, pose challenges that prompt-level

Event-Grounded Question Answering over Long Audio via Structured Retrieval

arXiv:2602.14612v4 Announce Type: replace-cross Abstract: Answering natural-language questions over multi-hour audio requires both event recognition and temporal grounding. Current large audio-languag

local-aiarxiv-cs-ai

Foundations of Practical Quantum Advantage in Quantum-Informed Machine Learning for Predicting Chaos

arXiv:2606.13422v2 Announce Type: replace-cross Abstract: We develop theoretical foundations for a practical quantum-advantage mechanism in quantum-informed machine learning for chaotic dynamical syst

FuseSampleAgg: One-Pass Neighborhood Estimation for Budgeted Knowledge-Graph Refresh and Validation

model-releasesarxiv-cs-lg

arXiv:2511.13645v2 Announce Type: replace Abstract: Operational knowledge-graph (KG) pipelines in networking and cybersecurity increasingly need to refresh embeddings under strict time, memory, and au

Hessian-augmented Supervised Learning for Hamilton-Jacobi-Bellman PDEs

arXiv:2606.23827v1 Announce Type: cross Abstract: A data-driven method is developed for approximating value functions in deterministic optimal control problems with nonlinear control-affine dynamics.

I decided to run my knowledge base inside a @Cloudflare Worker👀 How? Surprisingly easily: • Spin up a @qdrant_engine cluster and grab the c…

I decided to run my knowledge base inside a @Cloudflare Worker👀 How? Surprisingly easily: • Spin up a @qdrant_engine cluster and grab the credentials • Process incoming files at the edge: parse with @

agentsjerry-liu--x

Efficient Document Tampering Localization with Multi-Level Discrepancy Features and Unified DCT-Quantization Embedding

arXiv:2606.22285v1 Announce Type: new Abstract: Localizing document tampering is extremely challenging, as manipulations are crafted to appear visually consistent and often leave only subtle traces th

local-aiarxiv-cs-cv

Industry

End-to-End RAG Workflow: How Retrieval Augmented Generation Works

Retrieval Augmented Generation (RAG) is a technique that combines information retrieval with generative AI to enhance model outputs by fetching relevant external documents or data before generating re

industrydatabricks

Faithful Grounded Visual Reasoning via Learned Proxy-Tokens

arXiv:2606.23354v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success in Visual Question Answering (VQA), yet their 'black-box' nature hinders deplo

Federated learning with heavy-tailed gradient noise and communication noise: a variance-reduction based algorithm

arXiv:2606.22466v1 Announce Type: new Abstract: Federated learning (FL) is an emerging distributed machine learning paradigm that enables local devices to jointly train a global model while keeping da

local-aiarxiv-cs-lg

Log Analytics is now Observability Analytics: Query logs and traces with SQL

To effectively operate and troubleshoot applications, developers and site reliability engineers (SREs) need to understand the full context of their system's behavior, typically as part of their loggin

agentsgoogle-cloud-ai

MedFedPure: A Medical Federated Framework with MAE-based Detection and Diffusion Purification for Inference-Time Attacks

arXiv:2511.11625v2 Announce Type: replace Abstract: Artificial intelligence (AI) has shown great potential in medical imaging, particularly for brain tumor detection using Magnetic Resonance Imaging (

local-aiarxiv-cs-lg