All entries

BiMind: A Dual-Head Reasoning Model with Attention-Geometry Adapter for Incorrect Information Detection

arXiv:2604.06022v2 Announce Type: replace Abstract: Incorrect information poses significant challenges by disrupting content veracity and integrity, yet most detection approaches struggle to jointly b

researcharxiv-cs-cl

Local Ai

BIT.UA-AAUBS at ArchEHR-QA 2026: Evaluating Open-Source and Proprietary LLMs via Prompting in Low-Resource QA

DGX agent

arXiv:2605.03618v1 Announce Type: new Abstract: This paper presents the joint participation of the BIT.UA and AAUBS groups in the ArchEHR-QA 2026 shared task, which focuses on clinical question answer

local-aiarxiv-cs-cl

6 May 2026

Industry

Boost Security acquires SecureIQx and Korbit, adds $4M in new funding

Application security startup Boost Security Inc. today announced two acquisitions and an additional 4 million in funding as it builds out what it pitches as an artificial intelligence-native defense p

industrysiliconangle

Boosting Team Modeling through Tempo-Relational Representation Learning

arXiv:2507.13305v2 Announce Type: replace Abstract: Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and Social Sciences. Although a variety of computationa

applicationsarxiv-cs-lg

Bootstrapped Mixed Rewards for RL Post-Training: Injecting Canonical Action Order

arXiv:2512.04277v3 Announce Type: replace Abstract: Post-training with reinforcement learning (RL) typically optimizes a single scalar objective and ignores structure in how solutions are produced. We

safetyarxiv-cs-lg

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

arXiv:2605.03148v1 Announce Type: new Abstract: Reliable wildfire spread prediction is vital for risk-aware emergency planning, yet most deep learning models lack principled uncertainty quantification

researcharxiv-cs-cv

Bridging the Embodiment Gap: Disentangled Cross-Embodiment Video Editing

model-releasesarxiv-cs-ro

arXiv:2605.03637v1 Announce Type: new Abstract: Learning robotic manipulation from human videos is a promising solution to the data bottleneck in robotics, but the distribution shift between humans an

Bristol Myers Squibb's Massachusetts facility boosted drug production volume for clinical and commercial use by ~40% with AI, a bright spot in US manufacturing (Farah Stockman/New York Times)

Farah Stockman / New York Times: Bristol Myers Squibb's Massachusetts facility boosted drug production volume for clinical and commercial use by ~40% with AI, a bright spot in US manufacturing — A Bri

applicationstechmeme

Builder Plan: for the stage between prototype and scale

Builder Plan is Pinecone’s $20/month flat-rate pricing tier built for builders who’ve outgrown Starter but aren’t ready for usage-based pricing. It adds capacity for dev/staging/production workflows,

applicationspinecone

Tools

Builder tier. $20/month, flat. Pricing should match the stage of building, not just the scale of it. For the stretch when free feels tight b…

Builder tier. $20/month, flat. Pricing should match the stage of building, not just the scale of it. For the stretch when free feels tight but you're not yet at usage-based scale. 10 indexes, 1,000 na

toolspinecone--x

Calibration of the underlying surface parameters for urban flood using latent variables and adjoint equation

model-releasesarxiv-cs-lg

arXiv:2605.02959v1 Announce Type: new Abstract: Calibrating the urban underlying surface parameters is crucial for urban flood simulation. We formulate the parameter calibration problem into an optimi

Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

arXiv:2605.02690v1 Announce Type: cross Abstract: Hyperledger Fabric performance depends on many interacting configuration parameters, making manual tuning difficult. We study automated throughput tun

Can Blockchains Reliably Train Machine Learning Models?

arXiv:2307.07066v2 Announce Type: replace-cross Abstract: Large proof of work (PoW) networks allow anyone to earn rewards by running computation-intensive hash puzzles for profit, yet they typically c

Can Multimodal Large Language Models Understand Pathologic Movements? A Pilot Study on Seizure Semiology

arXiv:2605.03352v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated robust capabilities in recognizing everyday human activities, yet their potential for analyzi

researcharxiv-cs-cv

Can Semantic Methods Enhance Team Sports Tactics? A Methodology for Football with Broader Applications

arXiv:2601.00421v2 Announce Type: replace Abstract: This paper explores how semantic-space reasoning, traditionally used in computational linguistics, can be extended to tactical decision-making in te

Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests

arXiv:2508.14936v3 Announce Type: replace-cross Abstract: Synthetic data holds substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns.

applicationsarxiv-cs-lg

Local Ai

Can you change the resolution of the output-video when using WanAnimate?

local-air-stablediffusion

I don't have the ability to directly access and read the content from that Reddit URL. To provide an accurate factual summary for your knowledge base, I would need to search for this specific discussi

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

model-releasesarxiv-cs-lg

arXiv:2512.13913v3 Announce Type: replace Abstract: Out-of-equilibrium quantum many-body systems exhibit rapid correlation buildup that underlies many emerging phenomena. Exact wave-function methods t

Cascade Token Selection for Transformer Attention Acceleration

arXiv:2605.03110v1 Announce Type: new Abstract: A method is presented for reducing the cost of representative token selection in transformer attention layers by exploiting the coherence of the represe

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems

arXiv:2605.01758v1 Announce Type: new Abstract: Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulne

Causal Software Engineering: A Vision and Roadmap

model-releasesarxiv-cs-ai

arXiv:2605.02454v1 Announce Type: cross Abstract: Software engineering increasingly involves making high-stakes decisions under uncertainty, using signals from code, field data, and socio-technical pr

Tutorials

CBV: Clean-label Backdoor Attacks on Vision Language Models via Diffusion Models

arXiv:2605.02202v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved remarkable success in tasks such as image captioning and visual question answering (VQA). However, as their

tutorialsarxiv-cs-ai

CC-OCR V2: Benchmarking Large Multimodal Models for Literacy in Real-world Document Processing

model-releasesarxiv-cs-cl

arXiv:2605.03903v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently shown strong performance on Optical Character Recognition (OCR) tasks, demonstrating their promising capabi

CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation

arXiv:2605.00930v1 Announce Type: cross Abstract: In this work, we introduce CellxPert, a scalable multimodal foundation model that unifies single-cell and spatial multi-omics within a common represen

Industry

CEO of @huggingface, @ClementDelangue, is joining us at #DASH2026 for a fireside chat with Datadog CEO Olivier Pomel. They’ll discuss the ri…

CEO of @huggingface, @ClementDelangue, is joining us at #DASH2026 for a fireside chat with Datadog CEO Olivier Pomel. They’ll discuss the rise of open AI ecosystems, how Hugging Face has scaled a glob

industryclem-delangue--x

Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestation

arXiv:2605.01037v2 Announce Type: cross Abstract: We present a certified purity architecture that converts governance enforcement in cognitive workflow systems from a runtime convention into a structu

Tutorials

Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding

arXiv:2512.17817v3 Announce Type: replace Abstract: While 3DGS has emerged as a high-fidelity scene representation, encoding rich, general-purpose features directly from its primitives remains under-e

tutorialsarxiv-cs-cv

Local Ai

Chrome’s AI features may be hogging 4GB of your computer storage

Google Chrome may be taking up more of your storage than expected thanks to a large on-device AI model file that, in some cases, is being automatically downloaded to the browser's system folders. User

local-aithe-verge-ai

CLAPS: Aleatoric-Epistemic Scaling via Last-Layer Laplace for Conformal Regression

arXiv:2512.01384v4 Announce Type: replace Abstract: Conformal regression provides finite-sample marginal coverage, but it does not by itself determine how interval width should adapt across heterogene

Claude Desktop 3P Gateway

Claude Desktop has a third-party inference feature that lets you replace Anthropic's API with any model provider, including a local AI model running entirely on your machine. This feature can be activ

model-releasesr-ollama

Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents

arXiv:2604.06132v2 Announce Type: replace Abstract: Large language models are increasingly deployed as autonomous agents for multi-step workflows in real-world software environments. However, existing

.@Clay uses LangSmith to manage 300M agent runs a month, with an average 10-30 steps each. @hwchase17’s conversation with Clay’s Head of AI …

.@Clay uses LangSmith to manage 300M agent runs a month, with an average 10-30 steps each. @hwchase17’s conversation with Clay’s Head of AI @jeffbarg on how they run this at scale → https://youtu.be/c

agentsharrison-chase--x

Client-Conditional Federated Learning via Local Training Data Statistics

arXiv:2603.11307v2 Announce Type: replace Abstract: Federated learning (FL) under data heterogeneity remains challenging: existing methods either ignore client differences (FedAvg), require costly clu

ClinicBot: A Guideline-Grounded Clinical Chatbot with Prioritized Evidence RAG and Verifiable Citations

arXiv:2605.00846v1 Announce Type: new Abstract: Clinical diagnosis requires answers that are accurate, verifiable, and explicitly grounded in official guidelines. While large language models excel at

agentsarxiv-cs-ai

C’mon BBC. Zilis was sharp as a tack on the stand, on her role in the OpenAI nonprofit board, and how she managed conflicts as they began …

C’mon BBC. Zilis was sharp as a tack on the stand, on her role in the OpenAI *nonprofit* board, and how she managed conflicts as they began to develop, and this (which is not really even news since it

safetygary-marcus--x

Co-Generative De Novo Functional Protein Design

arXiv:2605.00948v1 Announce Type: cross Abstract: De novo functional protein design aims to generate protein sequences that realize specified biochemical functions without relying on evolutionary temp

Code with Claude is happening now! ▪︎ 9:00AM - Keynote ▪︎ 10:30AM - What's new in Claude Code ▪︎ 11:15AM - Building on Claude at GitHub scal…

model-releasesboris-cherny--x

Code with Claude is happening now! ▪︎ 9:00AM - Keynote ▪︎ 10:30AM - What's new in Claude Code ▪︎ 11:15AM - Building on Claude at GitHub scale ▪︎ 12:00PM - Get to production faster with Managed Agents

Code World Model Preparedness Report

arXiv:2605.00932v1 Announce Type: cross Abstract: This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conduc

CoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making

arXiv:2605.01457v1 Announce Type: new Abstract: Generative models have emerged as a major paradigm for offline multi-agent reinforcement learning (MARL), but existing approaches require many iterative

agentsarxiv-cs-ai

Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging

arXiv:2605.02734v1 Announce Type: new Abstract: Learning to Defer (L2D) enables a model to predict autonomously or defer to an expert, but prior work largely assumes flat label spaces. We study the fi

Collibra’s new AI Command Center promises to combat agentic hallucinations

Big data management startup Collibra BV is trying to position itself as the nerve center for artificial intelligence agents with the launch of its new AI Command Center offering. It’s designed to give

agentssiliconangle

Complex Equation Learner: Rational Symbolic Regression with Gradient Descent in Complex Domain

arXiv:2605.03841v1 Announce Type: new Abstract: Symbolic regression aims to discover interpretable equations from data, yet modern gradient-based methods fail for operators that introduce singularitie

Complexity Horizons of Compressed Models in Analog Circuit Analysis

arXiv:2605.02285v1 Announce Type: new Abstract: The deployment of Large Language Models (LLMs) for specialized engineering domains, such as circuit analysis, often faces a trade-off between reasoning

agentsarxiv-cs-ai

Complexity is not an intrinsic property of a problem. It's a property of the relationship between a problem and an observer. Once you know t…

researchfrancois-chollet--x

Complexity is fundamentally relative rather than absolute—it depends on the knowledge, perspective, and tools available to a particular observer rather than being an inherent feature of the problem it

Compress Then Adapt? No, Do It Together via Task-aware Union of Subspaces

model-releasesarxiv-cs-ai

arXiv:2605.02829v1 Announce Type: new Abstract: Adapting large pretrained models to diverse tasks is now routine, yet the two dominant strategies of parameter-efficient fine-tuning (PEFT) and low-rank

Conditional Diffusion Sampling

arXiv:2605.04013v1 Announce Type: cross Abstract: Sampling from unnormalized multimodal distributions with limited density evaluations remains a fundamental challenge in machine learning and natural s

Conditions for well-posed color recovery in scattering media

arXiv:2605.03837v1 Announce Type: new Abstract: Recovering scene color from images captured in scattering media is a fundamental inverse problem in optical imaging. Yet the problem is intrinsically il

researcharxiv-cs-cv

Conformalized Percentile Interval: Finite Sample Validity and Improved Conditional Performance

arXiv:2605.03233v1 Announce Type: cross Abstract: Conformal prediction provides distribution-free predictive intervals with finite-sample marginal coverage. However, achieving conditional validity and

applicationsarxiv-cs-lg