Search: “applications”

AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs

arXiv:2606.26173v1 Announce Type: new Abstract: Recent work shows that Large Language Models (LLMs) can act as semantic mutation operators for the evolutionary discovery of programs and proofs. Most c

agentsarxiv-cs-ai

Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis

DGX agent

arXiv:2606.26764v1 Announce Type: cross Abstract: Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shif

researcharxiv-cs-ai

26 Jun 2026

Auditing Framing-Sensitive Behavioral Instability in Large Language Models for Mental Health Interactions

arXiv:2606.26982v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into mental health support tools and other psychologically sensitive conversational app

researcharxiv-cs-ai

Automating Potential-based Reward Shaping with Vision Language Model Guidance

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

Budget-Aware Keyboardless Interaction

arXiv:2606.26508v1 Announce Type: cross Abstract: Interacting with computers typically relies on traditional input devices such as keyboards, mice, and monitors, which can be cumbersome for users seek

Hardware

CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs

arXiv:2606.26650v1 Announce Type: cross Abstract: In this paper, we present CAT-Q, Cost-efficient and Accurate Ternary Quantization, for compressing and accelerating LLMs. Unlike existing state-of-the

hardwarearxiv-cs-ai

Chai: Agentic Discovery of Cryptographic Misuse Vulnerabilities

arXiv:2606.26933v1 Announce Type: cross Abstract: AI-assisted vulnerability discovery has proven effective for bug classes like memory safety, where instrumentation confirms memory violations and effi

Compiler-Driven Approximation Tuning for Hyperdimensional Computing

arXiv:2606.26547v1 Announce Type: cross Abstract: As Moore's law reaches its physical and economic limits, domain-specific approaches are increasingly employed to accelerate machine learning workloads

DanceDuo: Bridging Human Movement and AI Choreography

arXiv:2606.26507v1 Announce Type: cross Abstract: In recent years, advancements in deep learning and generative models have revolutionized music-driven dance generation. This paper introduces a novel

DualEval: Joint Model-Item Calibration for Unified LLM Evaluation

arXiv:2606.26429v1 Announce Type: cross Abstract: Current LLM evaluation relies on two complementary but often disconnected signals: static benchmarks with objective correctness labels and arena-style

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

arXiv:2606.26120v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirect

Hardware

Event-based Gaze Control System for Accurate Real-time Spin Estimation in Professional Ball Games

arXiv:2606.26780v1 Announce Type: new Abstract: Spin plays a crucial role in many ball sports due to its effect on the trajectory of the ball. Vision-based estimation of the ball's spin during a game

hardwarearxiv-cs-cv

Generating Special Triangulations with Transformers

arXiv:2606.26660v1 Announce Type: cross Abstract: Triangulations, i.e., well-structured decompositions of geometric objects into triangle-like pieces, are central objects in many domains of mathematic

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

Improved Bounds for Private and Robust Alignment

arXiv:2512.23816v2 Announce Type: replace-cross Abstract: In this paper, we study the private and robust alignment of language models from a theoretical perspective by establishing upper bounds on the

Jailbreaking for the Average Jane: Choosing Optimal Jailbreaks via Bandit Algorithms for Automatically Enhanced Queries

arXiv:2606.26936v1 Announce Type: cross Abstract: With a profusion of jailbreaks for LLMs now widely known, a growing concern is that non-expert malicious actors ('the average Jane') could elicit acti

Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation

arXiv:2509.20008v2 Announce Type: replace Abstract: Penetration testing, the simulation of cyberattacks to identify security vulnerabilities, presents a sequential decision-making problem well-suited

safetyarxiv-cs-lg

LiveEdit: Towards Real-Time Diffusion-Based Streaming Video Editing

model-releasesarxiv-cs-cv

arXiv:2606.26740v1 Announce Type: new Abstract: Streaming video editing has made rapid progress, yet practical deployment is still limited by two core issues: maintaining stable backgrounds and non-ed

On-board Remote-Sensing Foundation Models for Unsupervised Change Detection of Disaster Events

arXiv:2606.27018v1 Announce Type: cross Abstract: Remote Sensing Foundation Models (RSFMs) have emerged as a powerful alternative to supervised models for Earth Observation, allowing satellites to aut

researcharxiv-cs-ai

One of my best uses of agentic loops has been personal health. I don't talk about it often because it's very personal. But here it goes in t…

One of my best uses of agentic loops has been personal health. I don't talk about it often because it's very personal. But here it goes in the hope it helps someone who's struggling. (I am not doing t

agentsdair-ai--x

Parametric Generalized Adaptive Moment Features (PG-AMF) for Bearing Fault Diagnosis and Machine Health Monitoring

model-releasesarxiv-cs-ai

arXiv:2606.26317v1 Announce Type: cross Abstract: Accurate fault diagnosis of rolling element bearings in rotating machinery is considered essential for ensuring industrial safety and enabling predict

PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models

arXiv:2606.26694v1 Announce Type: new Abstract: Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to ex

safetyarxiv-cs-cv

Predicting Fruit Quality with a Hybrid Machine Learning and Image Processing Approach

arXiv:2606.26165v1 Announce Type: new Abstract: Fruit spoilage is a significant issue in agriculture, leading to substantial economic losses. Addressing this, our study introduces a hybrid approach co

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP

model-releasesarxiv-cs-ai

arXiv:2606.26794v1 Announce Type: cross Abstract: CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text ali

Reconstruction Alignment Improves Unified Multimodal Models

arXiv:2509.07295v4 Announce Type: replace-cross Abstract: Unified multimodal models (UMMs) unify visual understanding and generation within a single architecture. However, conventional training relies

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs

model-releasesarxiv-cs-lg

arXiv:2606.27369v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) for training LLMs typically rely on ground-truth answers to assign rewards, limiting their applica

Scalable AI-assisted Workflow Management for Detector Design Optimization Using Distributed Computing

model-releasesarxiv-cs-ai

arXiv:2603.30014v2 Announce Type: replace-cross Abstract: The Production and Distributed Analysis (PanDA) system, originally developed for the ATLAS experiment at the CERN Large Hadron Collider (LHC),

Scalable Message-Passing Quantum Graph Neural Networks in the Weisfeiler-Leman Hierarchy

arXiv:2606.26873v1 Announce Type: cross Abstract: Graphs provide a natural language for relational data in chemistry, biology and optimisation. Graph neural networks (GNNs) have driven much of the rec

Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMs

arXiv:2508.03247v2 Announce Type: replace Abstract: Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals r

safetyarxiv-cs-cl

State-Specific Respiratory Signatures for Affective and Stress Recognition: Interpretable Respiratory Markers, Autocorrelation Lags, and Compact CNN Models

arXiv:2606.26723v1 Announce Type: cross Abstract: Respiratory activity is a direct and interpretable physiological channel for wearable stress and affective-state recognition, yet many studies emphasi

Industry

The best products at each layer will be built by teams who are obsessed with that layer.

This post argues that companies building the best products at any given layer of technology or infrastructure will be those whose teams are deeply focused and passionate about that specific layer rath

industryclem-delangue--x

Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection

arXiv:2412.09959v5 Announce Type: replace Abstract: Dataset distillation provides an effective approach to reduce memory and computational costs by optimizing a compact dataset that achieves performan

Uncertainty quantification via conformal prediction in data assimilation

arXiv:2606.27001v1 Announce Type: new Abstract: Quantifying the evolution of uncertainty is critical to both probabilistic forecasting and data assimilation in numerical weather prediction. In this st

Hardware

Vultr Clusters Now Supports CPUs in Addition to GPUs – Plus Other Enhancements

Vultr has expanded its Clusters offering to support CPU-based workloads alongside existing GPU support, enabling more diverse compute deployments. The announcement includes additional enhancements to

hardwarevultr

What to expect during RAISE Summit: Join theCUBE July 8-9

The artificial intelligence industry is entering a phase where the race for more capable models is taking a back seat to the economics of building and deploying AI infrastructure. This has resulted in

agentssiliconangle

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction

model-releasesarxiv-cs-cv

arXiv:2603.19964v3 Announce Type: replace Abstract: High-resolution geometric prediction is essential for robust perception in autonomous driving, robotics, and AR/MR, but current foundation models ar

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation

arXiv:2606.25476v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable performance across natural language processing tasks, yet their deployment in high-stakes appl

A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

arXiv:2606.26059v1 Announce Type: new Abstract: The laser welding full-penetration is of critical importance, as it constitutes one of the fundamental factors in achieving defect-free welded joints. A

Choose your own

'Choose Your Own' likely refers to a framework or methodology from Nous Research for customizable AI decision-making or model selection processes. Without access to the specific post content, this ent

researchnous-research--x

CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts

arXiv:2602.17663v2 Announce Type: replace-cross Abstract: HIPE-2026 is a CLEF evaluation lab dedicated to person-place relation extraction from noisy, multilingual historical texts. Building on the HI

Clifford Kolmogorov-Arnold Networks

arXiv:2602.05977v2 Announce Type: replace Abstract: We introduce Clifford Kolmogorov-Arnold Network (ClKAN), a flexible and efficient architecture for function approximation in arbitrary Clifford Alge

Confidence Sequences for Online Statistical Model Checking of Markov Decision Processes

arXiv:2606.25797v1 Announce Type: new Abstract: Markov decision processes (MDPs) are a classic model of decision making under uncertainty, exhibiting both non-deterministic choice as well as probabili

researcharxiv-cs-ai

Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities

arXiv:2606.25320v1 Announce Type: cross Abstract: Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Inform

Tools

Deep Agents and OpenCode are now available in the AI SDK Harness

Vercel has released Deep Agents and OpenCode adapters for the AI SDK Harness, expanding the framework's integration capabilities. These new adapters enable developers to leverage Deep Agents and OpenC

toolsvercel-blog

DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation

arXiv:2606.26058v1 Announce Type: new Abstract: Open domain subject-driven text-to-video (S2V) generation has drawn significant interest in academia and industry. Open domain S2V mainly involves two s

Dream at SemEval-2026 Task 13: SALSA for Single-Pass Machine-Generated Code Detection

arXiv:2606.25102v1 Announce Type: new Abstract: Large language models have transformed code generation, raising concerns around authorship, assessment integrity, and software trust. SemEval-2026 Task

DSP-SLAM++: A Unified Framework for Multi-Class, High-Fidelity Object SLAM in the Wild

arXiv:2606.25953v1 Announce Type: cross Abstract: Existing object-aware SLAM systems force a trade-off between real-time performance, multi-class support, and the generation of high-fidelity, semantic

agentsarxiv-cs-cv

Dual Distribution Estimation for Zero-shot Noisy Test-Time Adaptation with VLMs

model-releasesarxiv-cs-cv

arXiv:2606.25758v1 Announce Type: new Abstract: While test-time adaptation (TTA) empowers vision-language models to adapt without costly retraining, it remains highly vulnerable to out-of-distribution