All entries

ChronoLock: Protecting Videos from Unauthorized Text-to-Video Personalization

model-releasesarxiv-cs-cv

arXiv:2606.21146v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made it increasingly easy to synthesize realistic and temporally coherent videos, while recent personalization

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

CIExplainer++: Generating Causal and Interpretable Explanations for Graph Neural Networks

DGX agent

arXiv:2606.20747v1 Announce Type: new Abstract: Explainable Artificial Intelligence aims to make black-box models more trustworthy by presenting, in a human-understandable manner, the elements that le

researcharxiv-cs-lg

23 Jun 2026

Circuit realization and hardware linearization of monotone operator equilibrium networks

arXiv:2509.13793v2 Announce Type: replace-cross Abstract: It is shown that the port behavior of a resistor-diode network corresponds to the solution of a ReLU monotone operator equilibrium network (a

Circuit Synchronization Precedes Generalization: A Causal Precursor to Grokking

arXiv:2606.12966v2 Announce Type: replace Abstract: Grokking is the delayed generalisation phenomenon where a transformer trained on modular arithmetic abruptly transitions from near-chance to near-pe

Hardware

CITADEL: CSI-Based Jamming Detection and Open-Set Classification for IIoT Networks

arXiv:2606.22939v1 Announce Type: cross Abstract: Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things (IIoT) networks. Existing detection and

hardwarearxiv-cs-lg

CLAR: Learning 3D Representations for Robotic Manipulation by Fusing Masked Reconstruction with Multi-Level Contrastive Alignment

arXiv:2507.08262v2 Announce Type: replace-cross Abstract: The spatial information inherent in 3D point clouds is crucial for robotic manipulation. However, existing 3D pre-training methods face a fund

safetyarxiv-cs-cv

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. I…

model-releasesboris-cherny--x

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. It has excellent memory and access to your data, so it can be

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these …

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these are some of my favorites 🧵 Introducing Claude Tag, a new way

model-releasesthariq--x

ClayBuddy: A Framework, Evaluation, & Mitigation of Coding Agent Failures

arXiv:2606.19380v2 Announce Type: replace-cross Abstract: Software engineering and deployment are increasingly delegated to AI coding agents. The scale of their adoption is surfacing rare, but highly

Agents

ClickHouse brings real-time analytics to agentic AI

The growing use of AI agents throughout the enterprise is forcing a thorough reevaluation of the data layer. This shift is driven by the need for millisecond responses that enable agents to make decis

agentssiliconangle

CLIP-guided Diffusion Model for Backdoor Generation in Sensor-based Human Activity Recognition

arXiv:2606.22837v1 Announce Type: new Abstract: Sensors are critical components of modern intelligent devices. The proliferation of the Internet of Things (IoT) and wearable mobile devices has enabled

Clipping the Price of Adaptivity at the Tail

arXiv:2606.22669v1 Announce Type: new Abstract: Adaptive stochastic convex optimization (SCO) methods face a fundamental ``price of adaptivity'' barrier: under the standard set of assumptions, they ca

Cloak: Zero-Shot Cross-Embodiment Manipulation by Masking the End-Effector from the VLA

arXiv:2606.22836v1 Announce Type: new Abstract: We present Cloak, a training recipe that endows a Vision-Language-Action (VLA) model with zero-shot cross-embodiment transfer by cloaking the end-effect

researcharxiv-cs-ro

CLoE: Expert Consistency Learning for Robust Missing Modality Segmentation

arXiv:2603.09316v2 Announce Type: replace Abstract: Multimodal medical image segmentation often faces missing modalities at inference, which induces disagreement among modality experts and makes fusio

researcharxiv-cs-cv

Closed-Loop Verbal Reinforcement Learning for Task-Level Robotic Planning

arXiv:2603.22169v2 Announce Type: replace Abstract: We propose a new Verbal Reinforcement Learning (VRL) framework for interpretable task-level planning in mobile robotic systems operating under execu

safetyarxiv-cs-ro

Closing the Calibration Gap in Semantic Caching

arXiv:2606.19719v2 Announce Type: replace-cross Abstract: Semantic caching cuts LLM inference costs by serving a cached response to semantically similar queries. Standard practice evaluates these syst

Cluster-Specific Localized Drift Detection for Efficient Batch Model Adaptation under Controlled Distribution Shift

arXiv:2606.22026v1 Announce Type: new Abstract: Machine learning systems deployed in dynamic environments frequently operate under nonstationary data distributions, where controlled distribution shift

Local Ai

CMDS-AD: Cross-Modal Dual-Stream Decoupling for Few-Shot Anomaly Detection

arXiv:2606.20300v2 Announce Type: replace Abstract: Few-shot anomaly detection remains challenging due to limited training data. Multi-modal anomaly detection (MAD) offers a viable solution, leveragin

local-aiarxiv-cs-cv

CodePercept: Code-Grounded Visual STEM Perception for MLLMs

model-releasesarxiv-cs-cv

arXiv:2603.10757v2 Announce Type: replace Abstract: When MLLMs fail at Science, Technology, Engineering, and Mathematics (STEM) visual reasoning, a fundamental question arises: is it due to perceptual

Local Ai

CoDMD: Copula-aware Distribution Matching Distillation for Fast Video Generation

arXiv:2606.21982v1 Announce Type: new Abstract: Few-step distillation for video diffusion models has attracted significant attention, driven by the urgent demand for efficient deployment in real-world

local-aiarxiv-cs-cv

Tutorials

CogFormer: Learn All Your Models Once

arXiv:2603.20520v2 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) with neural networks has accelerated and transformed cognitive modeling workflows. SBI enables modelers to fi

tutorialsarxiv-cs-lg

CogniRoute: Learning to Route Social Evidence in Omni-Modal Models

arXiv:2606.20970v1 Announce Type: new Abstract: Omni-modal models can ingest video, audio, and text, but unified access to multiple modalities does not guarantee that a model uses the right evidence.

researcharxiv-cs-cv

Coherence Under Commitment: Probing Generalization and Vacuous Memorization in LLM Logical Reasoning

arXiv:2606.21083v1 Announce Type: cross Abstract: Large language models (LLMs) deployed for logical reasoning in knowledge-intensive domains exhibit a subtle but critical failure: coherence can be vac

Cohort-Anchored Foundation Models for Electronic Health Records: From Risk Scores to Auditable Peer Cohorts

arXiv:2606.21885v1 Announce Type: new Abstract: Foundation models have achieved remarkable performance across medical question answering, imaging, and electronic health record (EHR) tasks, yet reliabl

Collapsed Effective Operators for Higher-order Structures

arXiv:2606.23517v1 Announce Type: new Abstract: Higher-order structures are powerful relational modeling tools, yet existing spectral operators decompose the topology into separate ranks, leaving prac

Combinatorial Allocation Bandits with Nonlinear Arm Utility

arXiv:2603.07005v2 Announce Type: replace Abstract: A matching platform is a system that matches participants of different types, such as companies and job-seekers. In such a platform, maximizing matc

Applications

Combinatorial Sparse PCA Beyond the Spiked Identity Model

arXiv:2603.02607v2 Announce Type: replace-cross Abstract: Sparse PCA is one of the most well-studied problems in high-dimensional statistics. In this problem, we are given samples from a distribution

applicationsarxiv-cs-lg

Comparative Evaluation of Machine Learning and Deep Learning Models for Wound-Rotor Synchronous Motor Performance Prediction

arXiv:2606.21230v1 Announce Type: new Abstract: Wound rotor synchronous motors have emerged as a strong alternative that eliminates dependence on REEs. However, WRSM design requires the simultaneous o

Applications

Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning

arXiv:2602.22642v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) has substantially empowered Large Language Models (LLMs) to tackle complex reasoning tasks, yet the verbose nature of explici

applicationsarxiv-cs-lg

Agents

Compressing Observation History into Agent Memory: Distilling Transformers into Recurrent Transformers

arXiv:2606.21562v1 Announce Type: new Abstract: Transformers are AI's workhorse with strong performance in modeling sequential data, but their computational cost becomes prohibitive when processing lo

agentsarxiv-cs-cv

Compression and Retrieval: Implicit Memory Retrieval for Video World Models

arXiv:2606.23105v1 Announce Type: new Abstract: Video world models hold promise for simulating interactive environments, yet maintaining consistent long-term memory across complex camera trajectories

researcharxiv-cs-cv

Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation

arXiv:2606.22963v1 Announce Type: new Abstract: Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medical

safetyarxiv-cs-cv

Concept-Constrained Prompt Learning for Few-Shot CLIP Adaptation

arXiv:2606.22567v1 Announce Type: new Abstract: Few-shot prompt learning is an effective strategy for adapting CLIP to downstream tasks, but class-only prompt optimization can overfit base-class super

Conceptual Design of an Ecosystem for Real Farm Data Collection toward Agricultural AI Foundation Models

arXiv:2606.23258v1 Announce Type: new Abstract: Data scarcity is a fundamental challenge in developing AI and foundation models for agricultural robots. Existing open-source data platforms do not prov

researcharxiv-cs-ro

Hardware

Concordia: JIT-Compiled Persistent-Kernel Checkpointing for Fault-Tolerant LLM Inference

arXiv:2606.23521v1 Announce Type: cross Abstract: Long-running LLM agents keep valuable state resident on GPUs: KV caches, request schedulers, communication state, and sometimes online adapters. Losin

hardwarearxiv-cs-lg

Conditional Flow Matching for Visually-Guided Acoustic Highlighting

arXiv:2602.03762v3 Announce Type: replace-cross Abstract: Visually-guided acoustic highlighting seeks to rebalance audio in alignment with the accompanying video, creating a coherent audio-visual expe

Conditional neural control variates for variance reduction in Bayesian inverse problems

arXiv:2602.21357v2 Announce Type: replace-cross Abstract: Bayesian inference for inverse problems involves computing expectations under posterior distributions--e.g., posterior means, variances, or pr

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis

arXiv:2602.11973v2 Announce Type: replace Abstract: In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy.

safetyarxiv-cs-cv

Confidently Wrong: Severity-Aware Calibration of Prompt-Injection Detectors under Attack Shift

arXiv:2606.22659v1 Announce Type: cross Abstract: Prompt-injection detectors are deployed as guards: a model scores an input and a downstream system trusts or blocks it on that score. I study the conf

Local Ai

Configurable Algorithms for Histopathologic Cancer Detection on Quantum Hardware

arXiv:2606.21752v1 Announce Type: cross Abstract: Histopathologic cancer detection is challenging due to tissue variability, staining differences, and subtle visual distinctions between disease classe

local-aiarxiv-cs-cv

Conflict-Aware Switching for CBF-CLF-Based Multi-Goal Navigation

arXiv:2606.21577v1 Announce Type: new Abstract: Quadratic programs (QPs) using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are widely used for safe control in reach-and-avoi

safetyarxiv-cs-ro

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces

arXiv:2507.15741v2 Announce Type: replace-cross Abstract: This paper introduces a framework for uncertainty quantification in regression models defined on metric spaces. Using a proposed notion of hom

Tools

congrats @jxmnop ! so many aie speakers announcing companies ahead of the conference

This post congratulates @jxmnop on the announcement of multiple AI speakers revealing their company affiliations ahead of an upcoming conference, likely referencing significant industry participation

toolsswyx--x

ConnectomeBench2: A Unified Benchmark for Automated Connectomic Proofreading

model-releasesarxiv-cs-cv

arXiv:2606.21116v1 Announce Type: new Abstract: Proofreading--correcting segmentation errors in 3D brain reconstructions--is the rate-limiting step in synapse-resolution connectomics. We release Conne

Applications

Context-Aware Autoregressive Diffusion for Gloss-Wise Sign Language Production

arXiv:2606.21234v1 Announce Type: new Abstract: To generate natural and accurate sentence-level sign language, synthesizing the 'gloss', the fundamental semantic unit, is essential. However, most curr

applicationsarxiv-cs-cv

Continuous Behavioral Authentication via Multi-Expert BERT Log Analysis for Secure Data Sharing

arXiv:2606.21900v1 Announce Type: cross Abstract: Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid a

Continuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting

arXiv:2606.21021v1 Announce Type: new Abstract: Long-horizon spacecraft trajectory forecasting suffers from error accumulation due to the absence of corrective observations in the forecast regime, mak

Tutorials

Contrastive and Adaptive Multi-modal Masked Autoencoder for Spatial Transcriptomics

arXiv:2606.21156v1 Announce Type: new Abstract: The high cost of spatial transcriptomics (ST) has driven extensive studies into predicting gene expression directly from H&E histology images. However,

tutorialsarxiv-cs-cv