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Radar-Camera BEV Multi-Task Learning with Cross-Task Attention Bridge for Joint 3D Detection and Segmentation

arXiv:2604.12918v1 Announce Type: new Abstract: Bird's-eye-view (BEV) representations are the dominant paradigm for 3D perception in autonomous driving, providing a unified spatial canvas where detect

agentsarxiv-cs-cv

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Ramaphosa says South Africa does not have race laws, and @elonmusk and Starlink is not excluded because of such laws, but then he also says …

DGX agent

Ramaphosa says South Africa does not have race laws, and @elonmusk and Starlink is not excluded because of such laws, but then he also says that Musk and Starlink are welcome to do business in South A

industryelon-musk--x

15 Apr 2026

Ran ChatGPT Plus and Claude Pro side by side for 30 days, here's what I found as a daily ChatGPT user

A Reddit post from r/ChatGPT in which a longtime ChatGPT Plus user shares findings after running both ChatGPT Plus and Claude Pro simultaneously for 30 days. The post likely reflects a real-world comp

model-releasesr-chatgpt

RankOOD -- Class Ranking-based Out-of-Distribution Detection

model-releasesarxiv-cs-lg

arXiv:2511.19996v2 Announce Type: replace Abstract: We propose RankOOD, a rank-based Out-of-Distribution (OOD) detection approach based on training a model with the Placket-Luce loss, which is now ext

Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting

arXiv:2604.12834v1 Announce Type: cross Abstract: Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels

Read why Devin is different: https://cognition.ai/blog/devin-in-windsurf

Cognition AI published a blog post explaining how their AI software engineer Devin differs from and compares to Windsurf, likely addressing competitive positioning as AI coding assistants become an in

agentscognition-ai--x

Reading Between the Pixels: Linking Text-Image Embedding Alignment to Typographic Attack Success on Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.12371v1 Announce Type: new Abstract: We study typographic prompt injection attacks on vision-language models (VLMs), where adversarial text is rendered as images to bypass safety mechanisms

Reasoning about Intent for Ambiguous Requests

arXiv:2511.10453v3 Announce Type: replace-cross Abstract: Large language models often respond to ambiguous requests by implicitly committing to one interpretation, frustrating users and creating safet

safetyarxiv-cs-ai

ReasonXL: Shifting LLM Reasoning Language Without Sacrificing Performance

model-releasesarxiv-cs-cl

arXiv:2604.12378v1 Announce Type: new Abstract: Despite advances in multilingual capabilities, most large language models (LLMs) remain English-centric in their training and, crucially, in their produ

Red Teaming Large Reasoning Models

arXiv:2512.00412v4 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical

Rede Mater Dei de Saúde: Monitoring AI agents in the revenue cycle with Amazon Bedrock AgentCore

This post is cowritten by Renata Salvador Grande, Gabriel Bueno and Paulo Laurentys at Rede Mater Dei de Saúde. The growing adoption of multi-agent AI systems is redefining critical operations in heal

agentsaws-ml-blog

Redefining Quality Criteria and Distance-Aware Score Modeling for Image Editing Assessment

arXiv:2604.12175v1 Announce Type: new Abstract: Recent advances in image editing have heightened the need for reliable Image Editing Quality Assessment (IEQA). Unlike traditional methods, IEQA require

safetyarxiv-cs-cv

Tools

Reduced pricing for Turbo build machines

Vercel has reduced the pricing for Turbo build machines, which are high-performance compute options designed to accelerate build times for projects deployed on the Vercel platform. These machines offe

toolsvercel-blog

ReefMapGS: Enabling Large-Scale Underwater Reconstruction by Closing the Loop Between Multimodal SLAM and Gaussian Splatting

arXiv:2604.11992v1 Announce Type: cross Abstract: 3D Gaussian Splatting is a powerful visual representation, providing high-quality and efficient 3D scene reconstruction, but it is crucially dependent

researcharxiv-cs-cv

Refined Differentially Private Linear Regression via Extension of a Free Lunch Result

arXiv:2604.11820v1 Announce Type: cross Abstract: As data-privacy regulations tighten and statistical models are increasingly deployed on sensitive human-sourced data, privacy-preserving linear regres

ReflectCAP: Detailed Image Captioning with Reflective Memory

arXiv:2604.12357v1 Announce Type: new Abstract: Detailed image captioning demands both factual grounding and fine-grained coverage, yet existing methods have struggled to achieve them simultaneously.

RegD: Hierarchical Embeddings via Dissimilarity between Arbitrary Euclidean Regions

arXiv:2501.17518v3 Announce Type: replace-cross Abstract: Hierarchical data is common in many domains like life sciences and e-commerce, and its embeddings often play a critical role. While hyperbolic

applicationsarxiv-cs-ai

Register domains wherever you build: Cloudflare Registrar API now in beta

The Cloudflare Registrar API is now in beta. Developers and AI agents can search, check availability, and register domains at cost directly from their editor, their terminal, or their agent — without

agentscloudflare-ai

Relative Pose Estimation for Nonholonomic Robot Formation with UWB-IO Measurements (Extended version)

arXiv:2411.05481v5 Announce Type: replace Abstract: This article studies the problem of distributed formation control for multiple robots by using onboard ultra wide band (UWB) distance and inertial o

applicationsarxiv-cs-ro

Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models

arXiv:2604.12582v1 Announce Type: new Abstract: Recent Video Large Language Models (Video-LLMs) have demonstrated strong capability in video understanding, yet they still suffer from hallucinations. E

safetyarxiv-cs-cv

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

arXiv:2604.12753v1 Announce Type: new Abstract: Specular glare on reflective floors and glass surfaces frequently corrupts RGB-D depth measurements, producing holes and spikes that accumulate as persi

safetyarxiv-cs-ro

RePAIR: Interactive Machine Unlearning through Prompt-Aware Model Repair

arXiv:2604.12820v1 Announce Type: new Abstract: Large language models (LLMs) inherently absorb harmful knowledge, misinformation, and personal data during pretraining on large-scale web corpora, with

local-aiarxiv-cs-ai

Replicable Reinforcement Learning with Linear Function Approximation

arXiv:2509.08660v3 Announce Type: replace Abstract: Replication of experimental results has been a challenge faced by many scientific disciplines, including the field of machine learning. Recent work

Representation geometry shapes task performance in vision-language modeling for CT enterography

arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t

researcharxiv-cs-ai

Representing 3D Faces with Learnable B-Spline Volumes

arXiv:2604.12894v1 Announce Type: new Abstract: We present CUBE (Control-based Unified B-spline Encoding), a new geometric representation for human faces that combines B-spline volumes with learned fe

researcharxiv-cs-cv

Representing expertise accelerates learning from pedagogical interaction data

arXiv:2604.12195v1 Announce Type: new Abstract: Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals

researcharxiv-cs-cl

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism

arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,

researcharxiv-cs-ai

Industry

Restoring broken neural pathways

Restoring broken neural pathways What is neuron degeneration? Skyler, a machine learning engineer at Neuralink, shares how brain-computer interfaces could bypass neural pathways that are broken due to

industryelon-musk--x

Rethinking AI TCO: Why Cost per Token Is the Only Metric That Matters

Traditional data centers only stored, retrieved and processed data. In the generative and agentic AI era, these facilities have evolved into AI token factories. With AI inference becoming their primar

agentsnvidia-blog

Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

arXiv:2604.13016v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a core technique in the post-training of large language models, yet its training dynamics remain poorly unders

safetyarxiv-cs-ai

Rethinking Satellite Image Restoration for Onboard AI: A Lightweight Learning-Based Approach

arXiv:2604.12807v1 Announce Type: cross Abstract: Satellite image restoration aims to improve image quality by compensating for degradations (e.g., noise and blur) introduced by the imaging system and

applicationsarxiv-cs-ai

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization

arXiv:2604.12768v1 Announce Type: new Abstract: Federated learning (FL) is a distributed paradigm that coordinates massive local clients to collaboratively train a global model via stage-wise local tr

local-aiarxiv-cs-lg

Retrieval as a Decision: Training-Free Adaptive Gating for Efficient RAG

arXiv:2511.09803v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) improves factuality but retrieving for every query often hurts quality while inflating tokens and latency. We p

safetyarxiv-cs-cl

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models

arXiv:2501.13340v4 Announce Type: replace Abstract: Diffusion models (DMs) have recently demonstrated remarkable generation capability. However, their training generally requires huge computational re

researcharxiv-cs-cv

Revisiting the Reliability of Language Models in Instruction-Following

arXiv:2512.14754v2 Announce Type: replace-cross Abstract: Advanced LLMs have achieved near-ceiling instruction-following accuracy on benchmarks such as IFEval. However, these impressive scores do not

RFC: Solving the Metacognitive Deficit—A Modular Architecture for Self-Auditing and Live Weight-Correction in Agentic Systems

This Reddit post (r/ollama) proposes a community RFC (Request for Comments) discussing a modular architectural framework designed to address the 'metacognitive deficit' in agentic LLM systems — specif

agentsr-ollama

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation

arXiv:2604.12219v1 Announce Type: cross Abstract: Video Diffusion Transformers have revolutionized high-fidelity video generation but suffer from the massive computational burden of self-attention. Wh

local-aiarxiv-cs-ai

Rippling AI was the most successful launch we've ever done. On the heels of this launch, Rippling's revenue is now growing 78% YoY (at ARR o…

Rippling AI was the most successful launch we've ever done. On the heels of this launch, Rippling's revenue is now growing 78% YoY (at ARR over $1 Billion). And this growth rate has now increased, eve

agentsharrison-chase--x

Risk-Calibrated Learning: Minimizing Fatal Errors in Medical AI

arXiv:2604.12693v1 Announce Type: new Abstract: Deep learning models often achieve expert-level accuracy in medical image classification but suffer from a critical flaw: semantic incoherence. These hi

safetyarxiv-cs-cv

Tutorials

RLGT: A reinforcement learning framework for extremal graph theory

arXiv:2602.17276v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a subfield of machine learning that focuses on developing models that can autonomously learn optimal decision-making

tutorialsarxiv-cs-lg

RMGS-SLAM: Real-time Multi-sensor Gaussian Splatting SLAM

arXiv:2604.12942v1 Announce Type: new Abstract: Real-time 3D Gaussian splatting (3DGS)-based Simultaneous Localization and Mapping (SLAM) in large-scale real-world environments remains challenging, as

applicationsarxiv-cs-ro

Robotic Manipulation is Vision-to-Geometry Mapping (f(v) rightarrow G): Vision-Geometry Backbones over Language and Video Models

arXiv:2604.12908v1 Announce Type: new Abstract: At its core, robotic manipulation is a problem of vision-to-geometry mapping (f(v) rightarrow G). Physical actions are fundamentally defined by geometri

applicationsarxiv-cs-ro

Robotic Nanoparticle Synthesis via Solution-based Processes

arXiv:2604.12169v1 Announce Type: new Abstract: We present a screw geometry-based manipulation planning framework for the robotic automation of solution-based synthesis, exemplified through the prepar

researcharxiv-cs-ro

Robust Explanations for User Trust in Enterprise NLP Systems

arXiv:2604.12069v1 Announce Type: cross Abstract: Robust explanations are increasingly required for user trust in enterprise NLP, yet pre-deployment validation is difficult in the common case of black

Robust Federated Inference

arXiv:2510.00310v3 Announce Type: replace Abstract: Federated inference, in the form of one-shot federated learning, edge ensembles, or federated ensembles, has emerged as an attractive solution to co

local-aiarxiv-cs-lg

Robust gene prioritization for Dietary Restriction via Fast-mRMR Feature Selection techniques

arXiv:2511.21211v3 Announce Type: replace Abstract: Gene prioritization (identifying genes potentially associated with a biological process) is increasingly tackled with Artificial Intelligence. Howev

Robust Optimization for Mitigating Reward Hacking with Correlated Proxies

arXiv:2604.12086v1 Announce Type: new Abstract: Designing robust reinforcement learning (RL) agents in the presence of imperfect reward signals remains a core challenge. In practice, agents are often

safetyarxiv-cs-lg

Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearities

arXiv:2604.12079v1 Announce Type: cross Abstract: Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability