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Beyond Explained Variance: A Cautionary Tale of PCA

arXiv:2605.13520v1 Announce Type: cross Abstract: We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via

Beyond Individual Mimicry: Constructing Human-Like Social network with Graph-Augmented LLM Agents

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DGX agent

arXiv:2605.12512v1 Announce Type: cross Abstract: Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade soci

local-aiarxiv-cs-ai

14 May 2026

Beyond Oversquashing: Understanding Signal Propagation in GNNs Via Observables

arXiv:2605.13383v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) perform computations on graphs by routing the signal between graph regions using a graph shift operator or a message passin

Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training

arXiv:2605.13652v1 Announce Type: cross Abstract: Pre-training large language models is dominated by the memory cost of storing full-rank weights, gradients, and optimizer states. Low-rank pre-trainin

researcharxiv-cs-ai

Beyond Softmax: A Natural Parameterization for Categorical Random Variables

arXiv:2509.24728v2 Announce Type: replace Abstract: Latent categorical variables are frequently found in deep learning architectures. They can model actions in discrete reinforcement-learning environm

Beyond VMAF: Towards Application-Specific Metrics for Teleoperation Video

arXiv:2605.13525v1 Announce Type: cross Abstract: Automated driving has made remarkable progress, yet situations still arise where human intervention is necessary. Teleoperation provides a scalable so

safetyarxiv-cs-ro

Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models

model-releasesarxiv-cs-cv

arXiv:2603.05582v2 Announce Type: replace-cross Abstract: The issue of algorithmic biases in deep learning has led to the development of various debiasing techniques, many of which perform complex tra

Applications

Big increases in message discipline across all the AI labs in recent weeks, an inevitable outcome of the labs being subject to increased scr…

applicationsethan-mollick--x

Big increases in message discipline across all the AI labs in recent weeks, an inevitable outcome of the labs being subject to increased scrutiny. Much more boring than the oracular mutterings or Disc

big launches today!

model-releasesharrison-chase--x

big launches today! 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests

BioSEN: A Bio-acoustic Signal Enhancement Network for Animal Vocalizations

arXiv:2605.12534v1 Announce Type: cross Abstract: Most work in audio enhancement targets human speech, while bioacoustics is less studied due to noisy recordings and the distinct traits of animal soun

BiPneu: Design and Control of a Bipolar-Pressure Pneumatic System for Soft Robots

arXiv:2605.12804v1 Announce Type: new Abstract: Positive-negative pressure regulation is critical to soft robotic actuators, enabling large motion ranges and versatile actuation modes. However, achiev

researcharxiv-cs-ro

BlitzGS: City-Scale Gaussian Splatting at Lightning Speed

arXiv:2605.13794v1 Announce Type: cross Abstract: We present BlitzGS, a distributed 3DGS framework that reduces active Gaussian workload for fast city-scale reconstruction. BlitzGS manages this worklo

safetyarxiv-cs-cv

Block-wise Adaptive Caching for Accelerating Diffusion Policy

arXiv:2506.13456v2 Announce Type: replace Abstract: Diffusion Policy has demonstrated strong visuomotor modeling capabilities, but its high computational cost renders it impractical for real-time robo

BlockVLA: Accelerating Autoregressive VLA via Block Diffusion Finetuning

arXiv:2605.13382v1 Announce Type: new Abstract: While autoregressive (AR) Vision-Language-Action (VLA) models have demonstrated formidable reasoning capabilities in robotic tasks, their sequential dec

local-aiarxiv-cs-ro

Boomi and AWS built the guardrails for agents before anyone was asking for them

Agent governance has gone from niche concern to boardroom prerequisite — and the enterprises that saw it coming are now pulling ahead. The rise of agentic AI across enterprise operations has made gove

agentssiliconangle

BoostTaxo: Zero-Shot Taxonomy Induction via Boosting-Style Agentic Reasoning and Constraint-Aware Calibration

model-releasesarxiv-cs-ai

arXiv:2605.12520v1 Announce Type: cross Abstract: Taxonomy induction is crucial for organizing concepts into explicit and interpretable semantic hierarchies. While existing methods have achieved promi

Bounded-Input True Proportional Navigation for Impact-Time Control

arXiv:2605.13669v1 Announce Type: cross Abstract: This paper proposes a nonlinear guidance strategy capable of intercepting a constant-velocity, non-maneuvering target while strictly satisfying the pr

researcharxiv-cs-ro

Brain Tumor Classification in MRI Images: A Computationally Efficient Convolutional Neural Network

arXiv:2605.12560v1 Announce Type: cross Abstract: Improving patient outcomes depends on the prompt and accurate diagnosis of brain tumors, but manual MRI scan analysis is still time-consuming and unre

researcharxiv-cs-cv

BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability

arXiv:2605.13059v1 Announce Type: new Abstract: Clinical diagnostic workups typically follow a modality escalation pathway: after initial clinical evaluation, clinicians begin with routine structural

researcharxiv-cs-cv

Bridging Domain Gaps with Target-Aligned Generation for Offline Reinforcement Learning

arXiv:2605.13054v1 Announce Type: cross Abstract: Cross-domain offline reinforcement learning aims to adapt a policy from a source domain to a target domain using only pre-collected datasets, where en

Bridging the Missing-Modality Gap: Improving Text-Only Calibration of Vision Language Models

arXiv:2605.12517v1 Announce Type: cross Abstract: Vision-language models (VLMs) are often deployed on text-only inputs, although they are trained with images. We find that removing the vision modality

researcharxiv-cs-ai

Hardware

British inference chip startup Fractile bags $220M to accelerate token consumption

U.K.-based artificial intelligence inference chip startup Fractile Ltd. said today it has closed on a 220 million Series B round of funding. The company was founded in 2022 by the Oxford University-tr

hardwaresiliconangle

Tutorials

Build dashboards and automations from your Snowflake data for pipeline analysis, product usage, customer segments, and more. Admins maintain…

Build dashboards and automations from your Snowflake data for pipeline analysis, product usage, customer segments, and more. Admins maintain control over access, business definitions, and shared data

tutorialsperplexity--x

Building Interactive Real-Time Agents with Asynchronous I/O and Speculative Tool Calling

model-releasesarxiv-cs-lg

arXiv:2605.13360v1 Announce Type: new Abstract: There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applicat

built a bird search app to show off pinecone's full text search capabilities 2,079 bird articles, full-text keyword search, Gemini Embedding…

model-releasespinecone--x

built a bird search app to show off pinecone's full text search capabilities 2,079 bird articles, full-text keyword search, Gemini Embedding 2 for cross-modal visual search. the birds did not consent

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

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

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

agentsarxiv-cs-ai

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

agentsarxiv-cs-ai

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

safetyarxiv-cs-lg

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

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,

safetyarxiv-cs-lg

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

safetyarxiv-cs-lg

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

agentsarxiv-cs-ai

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