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Byzantine-Robust Distributed Sparse Learning Revisited

arXiv:2605.13283v1 Announce Type: new Abstract: We revisit Byzantine robust distributed estimation for high-dimensional sparse linear models. By combining local ell_1-regularized robust estimation wit

CA-GCL: Cross-Anatomy Global-Local Contrastive Learning for Robust 3D Medical Image Understanding

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DGX agent

arXiv:2605.13544v1 Announce Type: new Abstract: Fine-grained Vision-Language Pre-training (FVLP) demonstrates significant potential in 3D medical image understanding by aligning anatomy-level visual r

safetyarxiv-cs-cv

14 May 2026

CADDesigner: Conceptual CAD Model Generation with a General-Purpose Agent

arXiv:2508.01031v5 Announce Type: replace Abstract: Computer-Aided Design (CAD) is widely used for conceptual design and parametric 3D modeling, but typically requires a high level of expertise from d

Applications

Calibration-Free Gas Source Localization with Mobile Robots: Source Term Estimation Based on Concentration Measurement Ranking

arXiv:2605.13208v1 Announce Type: new Abstract: Efficient Gas Source Localization (GSL) in real-world settings is crucial, especially in emergency scenarios. Mobile robots equipped with low-cost, in-s

applicationsarxiv-cs-ro

California Gov. Gavin Newsom proposes a new 7.25% tax on web-based software sales, targeting $1.1B in state and local tax revenue in the upcoming budget year (Bloomberg)

Bloomberg: California Gov. Gavin Newsom proposes a new 7.25% tax on web-based software sales, targeting $1.1B in state and local tax revenue in the upcoming budget year — California Governor Gavin New

Can LLM Agents Simulate Dynamic Networks? A Case Study on Email Networks with Phishing Synthesis

arXiv:2605.12507v1 Announce Type: cross Abstract: While Large Language Model (LLM) multi-agent systems (MAS) offer a transformative approach to simulating human behavior in complex systems, it remains

CANTANTE: Optimizing Agentic Systems via Contrastive Credit Attribution

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

local-aiarxiv-cs-ai

Causal Fine-Tuning under Latent Confounded Shift

arXiv:2410.14375v3 Announce Type: replace Abstract: Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlati

Causal Learning with the Invariance Principle

arXiv:2605.13589v1 Announce Type: cross Abstract: Causal discovery, the problem of inferring the direction of causality, is generally ill-posed. We use the language of structural causal models (SCM) t

Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling

arXiv:2605.13646v1 Announce Type: cross Abstract: End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recentl

safetyarxiv-cs-ai

CAWI: Copula-Aligned Weight Initialization for Randomized Neural Networks

arXiv:2605.12580v1 Announce Type: new Abstract: Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing randomly initialized input-to-hidden weights, which permi

Centralized Adaptive Sampling for Reliable Co-Training of Independent Multi-Agent Policies

arXiv:2508.01049v2 Announce Type: replace Abstract: Independent on-policy policy gradient algorithms are widely used for multi-agent reinforcement learning (MARL) in cooperative and no-conflict games,

Cerebras co-founders CEO Andrew Feldman and CTO Sean Lie own stakes worth 3.2B and 1.7B, respectively, representing about 5.5% and 3% of the company (CJ Haddad/CNBC)

CJ Haddad / CNBC: Cerebras co-founders CEO Andrew Feldman and CTO Sean Lie own stakes worth 3.2B and 1.7B, respectively, representing about 5.5% and 3% of the company — The tech billionaires club has

Cerebras pops 68% in Nasdaq debut, pushing the AI chipmaker's market cap to $95 billion (Jordan Novet/CNBC)

Jordan Novet / CNBC: Cerebras pops 68% in Nasdaq debut, pushing the AI chipmaker's market cap to 95 billion … Cerebras Systems soared 68% in its Nasdaq debut on Thursday, closing at 311.07 after selli

Cerebras prices its shares at 185 ahead of biggest tech IPO in years, raising 5.5B

Cerebras Systems Inc. has officially priced its stock at 185 per share ahead of the most anticipated initial public offering of the year today, well above its expected range of between 150 and 160 per

industrysiliconangle

Cerebras shares closed up 68% at 311.07 in the company's Nasdaq debut after it raised 5.5B in the year's largest IPO, giving it a market value of $67B (Bloomberg)

Bloomberg: Cerebras shares closed up 68% at 311.07 in the company's Nasdaq debut after it raised 5.5B in the year's largest IPO, giving it a market value of 67B — Cerebras Systems Inc. shares jumped 6

Cerebras stock almost doubles from its initial offering price after the biggest tech IPO in years raised $5.5B

Updated with opening stock price: Cerebras Systems Inc. today opened trading as a public company at 350 a share, 89% above its offering price, as it kicked off what looks like a huge year for initial

industrysiliconangle

Certified Robustness under Heterogeneous Perturbations via Hybrid Randomized Smoothing

arXiv:2605.12876v1 Announce Type: new Abstract: Randomized smoothing provides strong, model-agnostic robustness certificates, but existing guarantees are limited to single modalities, treating continu

CHAL: Council of Hierarchical Agentic Language

arXiv:2605.12718v1 Announce Type: new Abstract: Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structu

ChannelKAN: Multi-Scale Dual-Domain Channel Prediction via Hybrid CNN-KAN Architecture

arXiv:2605.12553v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for improving the reliability and spectral efficiency of massive MIMO-OFDM systems in

local-aiarxiv-cs-ai

Tutorials

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting

arXiv:2509.23597v5 Announce Type: replace-cross Abstract: Time series forecasting remains a critical challenge across numerous domains, yet the effectiveness of complex models often varies unpredictab

tutorialsarxiv-cs-ai

Characterizing Universal Object Representations Across Vision Models

arXiv:2605.13675v1 Announce Type: new Abstract: Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. Ho

safetyarxiv-cs-cv

ChatSR: Multimodal Large Language Models for Scientific Formula Discovery

arXiv:2406.05410v3 Announce Type: replace Abstract: Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and

safetyarxiv-cs-ai

Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction

arXiv:2605.13262v1 Announce Type: new Abstract: Modern SMILES-based chemical language models obtain strong MoleculeNet performance by treating SMILES as generic text and compensating with multi-millio

Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety

arXiv:2605.13709v1 Announce Type: cross Abstract: Large Language Models (LLMs) are widely applied in educational practices, such as for generating children's stories. However, the generated stories ar

ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation

arXiv:2605.12857v1 Announce Type: cross Abstract: Existing API-based agentic systems for RTL code generation are fundamentally misaligned with industrial practice: they assume a golden testbench is av

Cisco announces record revenue and 4,000 layoffs in the same day

Cisco announced nearly 4,000 job cuts as part of a restructuring to shift investment toward artificial intelligence while simultaneously raising its annual revenue forecast after strong hyperscaler de

industryars-technica

CiteVQA: Benchmarking Evidence Attribution for Trustworthy Document Intelligence

model-releasesarxiv-cs-cv

arXiv:2605.12882v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have significantly advanced document understanding, yet current Doc-VQA evaluations score only the final answ

CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large VIsion-Language Models

arXiv:2605.13178v1 Announce Type: cross Abstract: In large vision-language models, visual tokens typically constitute the majority of input tokens, leading to substantial computational overhead. To ad

researcharxiv-cs-ai

Closing time

Today was closing arguments in the Musk v. Altman trial, and I almost feel bad writing about the unbelievable demolition derby I just witnessed. Steven Molo, Musk's lawyer, stumbled over his words. He

industrythe-verge-ai

Cloud CISO Perspectives: How Google + Wiz changes multicloud strategy for CISOs

model-releasesgoogle-cloud-ai

Welcome to the first Cloud CISO Perspectives for May 2026. Today, Vinod D’Souza, director, Office of the CISO, shares highlights from his RSA Conference fireside chat with Anthony Belfiore, chief stra

Clustering in pure-attention hardmax transformers and its role in sentiment analysis

arXiv:2407.01602v2 Announce Type: replace-cross Abstract: Transformers are extremely successful machine learning models whose mathematical properties remain poorly understood. Here, we rigorously char

CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem

arXiv:2605.13638v1 Announce Type: cross Abstract: A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum c

Code-Centric Detection of Vulnerability-Fixing Commits: A Unified Benchmark and Empirical Study

model-releasesarxiv-cs-lg

arXiv:2605.13138v1 Announce Type: cross Abstract: Automated detection of vulnerability-fixing commits (VFCs) is critical for timely security patch deployment, as advisory databases lag patch releases

CodeClash: Benchmarking Goal-Oriented Software Engineering

arXiv:2511.00839v2 Announce Type: replace-cross Abstract: Current benchmarks for coding evaluate language models (LMs) on concrete, well-specified tasks such as fixing specific bugs or writing targete

CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy

arXiv:2605.13038v1 Announce Type: cross Abstract: Geometric estimation including depth estimation and scene reconstruction is a crucial technique for colonoscopy which can provide surgeons with 3D spa

local-aiarxiv-cs-ai

Cognifold: Always-On Proactive Memory via Cognitive Folding

arXiv:2605.13438v1 Announce Type: new Abstract: Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cogni

Collaborating in Multi-Armed Bandits with Strategic Agents

arXiv:2605.13145v1 Announce Type: new Abstract: We study collaborative learning in multi-agent Bayesian bandit problems, where strategic agents collectively solve the same bandit instance. While multi

agentsarxiv-cs-lg

Collaborative Parameter Learning: Mitigating Forgetting via Parameter-Level Gradient Analysis

model-releasesarxiv-cs-lg

arXiv:2601.21577v2 Announce Type: replace Abstract: Catastrophic forgetting during knowledge injection impairs the ability of large language models to acquire new knowledge without overwriting previou

Color Constancy in Hyperspectral Imaging via Reduced Spectral Spaces

arXiv:2605.13306v1 Announce Type: new Abstract: Illuminant estimation aims to infer scene illumination from image measurements despite intrinsic ambiguities between surface reflectance and lighting. M

researcharxiv-cs-cv

Comfyui error Missing Models (1)AttributeError: module 'tensorflow' has no attribute 'Tensor'

local-air-stablediffusion

This error in ComfyUI occurs when the einops library encounters a broken TensorFlow installation while performing multi-backend type checks, even though ComfyUI itself is PyTorch-based. The primary so

Common sense prevails

Common sense prevails 🚨 BREAKING: The US Supreme Court has ruled 9-0 that freight brokers can be held LIABLE if they negligently hire unsafe trucking companies — including those with ILLEGAL ALIEN and

industryelon-musk--x

Compact 3D Gaussian Splatting For Dense Visual SLAM

model-releasesarxiv-cs-cv

arXiv:2403.11247v3 Announce Type: replace Abstract: Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes.

Compact Latent Manifold Translation: A Parameter-Efficient Foundation Model for Cross-Modal and Cross-Frequency Physiological Signal Synthesis

arXiv:2605.13248v1 Announce Type: cross Abstract: The analysis of physiological time series, such as electrocardiograms (ECG) and photoplethysmograms (PPG), is persistently hindered by modality and fr

Comparing tokens per second of common models

This Reddit post likely compares inference performance metrics across popular language models running on Ollama, measuring tokens per second as a key performance indicator. The post would help users a

local-air-ollama

Tools

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and me…

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics. It’s like a personal data science team, on call with

toolsperplexity--x

Applications

Conditional Compatibility Learning for Context-Dependent Anomaly Detection

arXiv:2601.22868v3 Announce Type: replace Abstract: Anomaly detection usually assumes that abnormality is an intrinsic property of an observation. A defect is a defect, and a rare object is rare, rega

applicationsarxiv-cs-cv

Tutorials

Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with 'nonconform'

arXiv:2605.13642v1 Announce Type: cross Abstract: Most anomaly detection systems output scores rather than calibrated decisions, leaving practitioners to choose thresholds heuristically and without cl

tutorialsarxiv-cs-lg