Search: “models”

JEDEL: Zero-Shot DNA-Encoded Library Design for Early-Stage Drug Discovery

arXiv:2606.23745v1 Announce Type: cross Abstract: We present JEDEL, a framework for generating synthesis-ready DNA-encoded libraries (DELs) directly from three-dimensional pharmacophore representation

safetyarxiv-cs-ai

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JupOtter: Cell-Level Bug Detection in Jupyter Notebooks

DGX agent

arXiv:2606.23877v1 Announce Type: cross Abstract: Jupyter Notebooks are an increasingly popular coding environment used across many domains, especially in Python-based data science and scientific comp

researcharxiv-cs-ai

24 Jun 2026

LecturaAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching

arXiv:2606.16428v2 Announce Type: replace-cross Abstract: Effective personalized AI-assisted learning demands systems that can not only generate accurate learner-specific educational materials, but al

safetyarxiv-cs-ai

Light-weight Pronunciation Assessment via Discrete Speech Token Surprisal

arXiv:2606.19910v2 Announce Type: replace Abstract: Training automated pronunciation assessment often relies on labeled learner errors or non-native corpora that are costly to collect. We propose a li

safetyarxiv-cs-cl

Local Ai

LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context

arXiv:2606.24585v1 Announce Type: new Abstract: While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with per

local-aiarxiv-cs-ai

Managing Task Execution for Unknown Workloads in Batteryless IoT: A Hardware-Agnostic Evaluation

arXiv:2606.24340v1 Announce Type: new Abstract: In recent years, the Internet of Things (IoT) paradigm has been shifting toward batteryless, energy-harvesting architectures. Sustaining reliable operat

agentsarxiv-cs-lg

Applications

MATCH: Flow Matching for Multi-View Anomaly Detection

arXiv:2606.24375v1 Announce Type: new Abstract: Detecting anomalies in industrial objects is an important topic for increasing production efficiency. More complex objects often require the analysis of

applicationsarxiv-cs-cv

Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles

arXiv:2505.02281v3 Announce Type: replace-cross Abstract: This paper explores the performance of a random Gaussian smoothing zeroth-order (ZO) scheme for minimising quasar-convex (QC) and strongly qua

MyoInteract: A Framework for Fast Prototyping of Biomechanical HCI Tasks using Reinforcement Learning

arXiv:2602.15245v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL)-based biomechanical simulations have the potential to revolutionise HCI research and interaction design, but curre

NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction

arXiv:2606.24087v1 Announce Type: new Abstract: Reconstructing continuous speech from scalp electroencephalography (EEG) remains fundamentally challenging. EEG provides a weak, spatially diffuse, and

Tutorials

NoContactNoWorries: Estimating Contact through Vision and Proprioception for In-Hand Dexterous Manipulation

arXiv:2606.24450v1 Announce Type: cross Abstract: Perceiving physical contact is fundamental to dexterous manipulation. While robots often rely on dedicated hardware tactile sensors, humans exhibit a

tutorialsarxiv-cs-ai

OmniPath: A Multi-Modal Agentic Framework for Auditing Wheelchair Accessibility

arXiv:2606.24129v1 Announce Type: new Abstract: For a wheelchair user, a standard blue line on a map is often a broken promise. While platforms like OpenStreetMap (OSM) successfully capture where a pa

agentsarxiv-cs-ai

Industry

One more thing. NEWS with @huggingface @ClementDelangue @durga_malladi

Clem Delangue, CEO of Hugging Face, announced a news update alongside Durga Malladi, likely regarding new developments, products, or initiatives from the company. The post was shared on X (formerly Tw

industryclem-delangue--x

Open-Vocabulary BEV Segmentation with 3D-Aware Geometric Constraints

arXiv:2606.24353v1 Announce Type: new Abstract: Bird's-eye view (BEV) perception fuses multi-camera images into a unified top-down representation for autonomous driving. Despite recent progress, state

agentsarxiv-cs-cv

pretty sick that i get to work with Jake every day on making continual learning + memory accessible at scale for every single agent one comm…

pretty sick that i get to work with Jake every day on making continual learning + memory accessible at scale for every single agent one common thread here is...the Trace a large part of Continual Lear

agentsharrison-chase--x

Local Ai

Quantum CT via Dynamic Interval Encoding and Prior-Balanced QUBO Reconstruction

arXiv:2606.24561v1 Announce Type: new Abstract: Quadratic unconstrained binary optimization (QUBO)-based quantum computed tomography (CT) casts reconstruction as a binary quadratic problem for quantum

local-aiarxiv-cs-cv

ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling

arXiv:2606.24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines. However, existi

agentsarxiv-cs-ai

RoBoSR: Structured Scene Representations for Embodied Robotic Reasoning

arXiv:2606.24338v1 Announce Type: new Abstract: Despite rapid progress, embodied reasoning under real-world variability remains challenging. Existing approaches rely on demonstration-driven sequential

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Applications

Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image

arXiv:2606.24138v1 Announce Type: new Abstract: Generating explicit 3D city assets from a single satellite image is important for digital twins, urban simulation, and geospatial intelligence. Unlike s

applicationsarxiv-cs-cv

Local Ai

SHERLOC: Structured Diagnostic Localization for Code Repair Agents

arXiv:2606.24820v1 Announce Type: new Abstract: LLM agents solve repository-level coding tasks through multi-turn tool use, but utilize half their budget on locating faults before editing. Dedicated l

local-aiarxiv-cs-cl

Similarity of Neural Network Representations in Superposition

arXiv:2604.00208v2 Announce Type: replace Abstract: Comparing internal representations is a central goal in neuroscience and machine learning, but standard linear alignment metrics (Representational S

safetyarxiv-cs-lg

SlipSense: Multimodal Sensing for Online Slip Detection in Legged Robots

arXiv:2606.24350v1 Announce Type: new Abstract: Legged robots rely on accurate ground interaction awareness to traverse variable terrains, such as slippery surfaces. Existing slip detection methods of

researcharxiv-cs-ro

Industry

Sources: Zhipu is considering a multibillion-dollar Hong Kong share sale after its stock surged 2,000% since its January IPO, pushing its market cap above $128B (Dong Cao/Bloomberg)

Dong Cao / Bloomberg: Sources: Zhipu is considering a multibillion-dollar Hong Kong share sale after its stock surged 2,000% since its January IPO, pushing its market cap above $128B — Chinese artific

industrytechmeme

The emergence of the web data infrastructure layer for AI

AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstru

researchmit-tech-review

Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback

arXiv:2606.24622v1 Announce Type: new Abstract: Training safe Reinforcement Learning (RL) systems is inherently challenging, with no guarantee of avoiding unwanted behaviors. The most effective defens

safetyarxiv-cs-ai

To enable creative-ideation and our other optional skills, run 'hermes skills config'

Nous Research recommends using the 'hermes skills config' command to enable creative-ideation and other optional skills in their system. This command appears to be a configuration tool for activating

researchnous-research--x

Training-free Cross-domain Few-shot Segmentation via Robust Semantic Representation and Matching

arXiv:2606.24297v1 Announce Type: new Abstract: Cross-domain Few-shot Segmentation (CD-FSS) aims to transfer knowledge learned from source domain to distinct target domains, segmenting unseen target c

Trustworthy Image Authentication using Forensic Knowledge Graphs

arXiv:2606.23917v1 Announce Type: new Abstract: Advances in generative AI have made image falsification highly realistic, demanding trustworthy authentication systems. Existing forensic detectors can

Uniform Sampling from High-dimensional Spectral Norm Balls

arXiv:2606.24134v1 Announce Type: cross Abstract: Motivated by an application in machine learning optimization, this paper focuses on the challenges of sampling a matrix uniformly from the unit spectr

Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent

arXiv:2606.24094v1 Announce Type: new Abstract: Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven

agentsarxiv-cs-cv

Varying Bundle Size Reactive Multi-Task Assignment using Selective Cost Estimation for Multi-Agent Systems

arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall

agentsarxiv-cs-ro

Visualizing 'We the People': Bridging the Perception Gap through Pluralistic Data Storytelling

arXiv:2606.24635v1 Announce Type: cross Abstract: Traditional visual data storytelling relies on binary graphics that depict two simplified groups in conflict. This can increase political polarization

Applications

ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering

arXiv:2606.24602v1 Announce Type: new Abstract: Despite remarkable progress in multimodal understanding, current MLLMs still exhibit limitations in video text understanding, particularly when semantic

applicationsarxiv-cs-cv

Weight-Space Geometry of Offline Reasoning Training

arXiv:2606.23740v1 Announce Type: cross Abstract: Offline reinforcement-learning losses (RFT, RIFT, DFT, Offline GRPO, DPO) are widely used to distill reasoning from large teachers into smaller studen

We’ve designed and built our first AI chip: Jalapeño. Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalape…

We’ve designed and built our first AI chip: Jalapeño. Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT,

agentsopenai--x

Industry

What if the answer was already in your data?

This Databricks blog post explores how organizations can leverage their existing data assets to find answers to business questions without requiring additional data collection or external sources. The

industrydatabricks

Which Spaces can be Embedded in L_p-type Reproducing Kernel Banach Space? A Characterization via Metric Entropy

arXiv:2410.11116v4 Announce Type: replace-cross Abstract: In this paper, we establish a novel connection between the metric entropy growth and the embeddability of function spaces into reproducing ker

Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks

This article discusses why Databricks leaders argue that the frontier AI ecosystem should remain open rather than closed, likely covering topics such as open-source AI development, the benefits of col

agentslatent-space

Tutorials

Zero-Day Exploitation of Vulnerability (CVE-2026-20245) in Cisco Catalyst SD-WAN Manager

Written by: Chester Sng, Pete Boonyakarn, Logeswaran Nadarajan Introduction In early 2026, Mandiant identified a threat actor targeting SD-WAN infrastructure at a service provider. After gaining initi

tutorialsgoogle-cloud-ai

3D Vessel Reconstruction from Sparse-View Dynamic DSA Images via Vessel Probability Guided Attenuation Learning

arXiv:2405.10705v3 Announce Type: replace-cross Abstract: Digital Subtraction Angiography (DSA) is one of the gold standards for vascular disease diagnosis. With the help of a contrast agent, time-res

agentsarxiv-cs-cv

A Causal DAG Prior for Synthetic Time-Series Classification Datasets

arXiv:2606.21776v1 Announce Type: new Abstract: A Prior-data fitted Network learns the posterior predictive induced by its training prior; bringing this paradigm to multivariate time-series classifica

Hardware

A Differentiable Atari VCS:A Complex, Fully Known Ground Truth for Explainable AI

arXiv:2606.22447v1 Announce Type: cross Abstract: Explanation requires ground truth: to verify an account of a system we must know its inner functioning-just what is missing where explainable AI (XAI)

hardwarearxiv-cs-lg

A statistical physics framework for optimal learning

arXiv:2507.07907v2 Announce Type: replace-cross Abstract: Learning is a complex dynamical process shaped by a range of interconnected decisions. Careful design of hyperparameter schedules for artifici

A Test-time Actor-Critic Approach to News Images Generation

arXiv:2606.21304v1 Announce Type: new Abstract: This paper introduces the CERTH-ITI solution for the MediaEval NewsImages 2026 challenge, which focuses on generating images related to news headlines.

A Viscosity Semigroup Framework for Stable Image Reconstruction

arXiv:2606.20620v1 Announce Type: new Abstract: Starting from the axiomatic formulation of scale-space theory, we develop a viscosity-solution framework for multiscale image representations arising fr

Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys

arXiv:2606.22112v1 Announce Type: new Abstract: The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcin

Hardware

ACEsplat: Accelerated 3D Gaussian Scene Regression via RGB and Poses Only

arXiv:2606.22091v1 Announce Type: new Abstract: Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external ge

hardwarearxiv-cs-ro

Adversarial Bandit Optimization with Globally Bounded Perturbations to Convex Losses

arXiv:2606.19891v2 Announce Type: replace Abstract: We study adversarial bandit optimization in which the loss functions may be non-convex and non-smooth. In each round, the learner selects an action