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ReconMIL: Synergizing Latent Space Reconstruction with Bi-Stream Mamba for Whole Slide Image Analysis

arXiv:2603.19925v2 Announce Type: replace-cross Abstract: Whole slide image (WSI) analysis heavily relies on multiple instance learning (MIL). While recent methods benefit from large-scale foundation

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Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers

DGX agent

arXiv:2606.21289v1 Announce Type: new Abstract: Nondestructive detection methods, based on vibrational spectroscopy, are vitally important in a wide range of applications including industrial chemistr

applicationsarxiv-cs-lg

23 Jun 2026

Industry

Record a skill

This article from Ben's Bites likely covers methods or tools for documenting and recording professional skills, possibly in the context of AI-assisted learning, portfolio building, or skill verificati

industryben-s-bites

Tools

Redesigned trace viewer for Vercel Workflows

Vercel has introduced a redesigned trace viewer for Vercel Workflows that improves the visualization and debugging experience for workflow executions. The updated interface likely provides enhanced vi

toolsvercel-blog

Applications

Reference-Free Assessment of Physical Consistency in World Model-based Video Generation

arXiv:2606.22363v1 Announce Type: cross Abstract: We introduce reference-free measures for evaluating the physical consistency of generated videos, combining relative and absolute approaches to assess

applicationsarxiv-cs-lg

ReFPO: Reflow Regularization for Flow Matching Policy Gradients

arXiv:2606.21086v1 Announce Type: new Abstract: We present Reflow-regularized Flow Matching Policy Gradients (ReFPO), a simple online RL method that adds explicit Reflow regularization to FPO for effi

Region-Specific Calibration Achieves Excellent Inter-Device Reliability for Smartphone Dermatology: A Multi-Device Benchmark on Korean Facial Skin

model-releasesarxiv-cs-cv

arXiv:2512.21988v3 Announce Type: replace-cross Abstract: Background: Smartphone-based dermatology requires inter-device colorimetric reliability that holds across calibration regimes, yet quantitativ

Reinforcement Learning-Based Traffic Signal Control for IoT-Enabled Intersections

arXiv:2606.22108v1 Announce Type: cross Abstract: Urban traffic congestion remains a persistent challenge in car-dependent cities, imposing significant economic and societal costs. Traffic signal syst

safetyarxiv-cs-lg

Agents

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

arXiv:2406.07884v2 Announce Type: replace-cross Abstract: Using partial knowledge of a quantum state to control multiqubit entanglement is a largely unexplored paradigm in the emerging field of quantu

agentsarxiv-cs-lg

Reinforcement learning to improve large language model-based automated code compliance systems

arXiv:2606.22402v1 Announce Type: cross Abstract: Large language model (LLM)-based approaches for automated code compliance (ACC) of building regulations are prone to generating incorrect and hallucin

Reinventing the zipper

With an adaptable fastener designed at CSAIL, pitching a tent or adjusting the cast for a broken bone could be almost as easy as zipping your coat. The researchers, led by associate professor Stefanie

researchmit-tech-review

Rejections Based on Predictive Uncertainty Enable Reliable Routine Soil Spectroscopy

arXiv:2606.21179v1 Announce Type: new Abstract: Soil properties relevant to agricultural and environmental applications are conventionally measured using elaborate laboratory methods involving physica

REKEY: Metadata-Grounded Visual-Key Regeneration for Contamination-Resilient VQA Evaluation

model-releasesarxiv-cs-cv

arXiv:2606.20736v1 Announce Type: new Abstract: Static visual question answering (VQA) benchmarks age quickly: Once the items leak into training corpora, scores can reflect memorization rather than ge

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems

arXiv:2606.20832v1 Announce Type: cross Abstract: Astrophysical simulations frequently address multi-scale, multi-physics problems through subsystem decomposition, problem-tailored integration schemes

Reliability-Guided Adaptive Ensembling for Robust Test-Time Adaptation

arXiv:2606.22351v1 Announce Type: cross Abstract: Test-time adaptation (TTA) can mitigate domain shift without source data, but it is highly brittle under adversarially contaminated test streams, wher

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

arXiv:2601.03357v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has become a standard approach to reconstruct and render photorealistic 3D head avatars. A major challenge is to religh

Remember what you did?: Learning Behavioral Memories for Partially Observable Object Manipulation

arXiv:2606.21188v1 Announce Type: new Abstract: Long horizon, contact-rich manipulation is inherently partially observable. This is as a single visual observation rarely captures a robot's full action

Render-FM: Feedforward Model for Real-time Photorealistic Volumetric Rendering

arXiv:2505.17338v2 Announce Type: replace Abstract: Photorealistic volumetric rendering of CT scans greatly benefits clinical workflows, yet neural approaches such as Neural Radiance Fields (NeRF) and

ReNIO: Reweighting Negative Trajectory Importance for LLM On-Policy Distillation

arXiv:2606.23104v1 Announce Type: new Abstract: On-policy distillation (OPD) improves LLM reasoning by training a student model on its own generated outputs, but standard OPD treats all student-genera

Repeated Shared Access Enables Grokking, but Edit Propagation Depends on a Fine-Grained Addressable Memory

arXiv:2606.20737v1 Announce Type: cross Abstract: We study factual edit propagation in a controlled synthetic knowledge-graph QA setting, comparing four architectures that cross loop recurrence with s

Industry

Report: Female cop shoots Jewish rabbi outside Pornhub office in Canada while hiding from Marxist gunman who killed immigrant officer named …

I can't verify the specific claims in this headline, and the incomplete title makes it unclear what incident is being referenced. This appears to be a sensationalized or satirical post from a parody a

industryelon-musk--x

Residue-Level Attributions in Protein Language Models Do Not Recover Allergen Epitopes

arXiv:2606.22181v1 Announce Type: new Abstract: Deep allergenicity classifiers are increasingly used in safety screening of novel foods, and recent protein language models have substantially improved

Resolving Multi-Target Association in OFDM-based ISAC via Vision-aided Multi-Modal Learning

arXiv:2606.22195v1 Announce Type: new Abstract: Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems commonly extract target parameters by peak-s

Rethinking Molecular Graph Backdoors under Chemistry-aware Admission

arXiv:2606.23361v1 Announce Type: new Abstract: Backdoor attacks on molecular graph neural networks (GNNs) are typically evaluated as abstract graph edits, but real molecular learning pipelines do not

Rethinking Object-Centric Representations for Video Dynamics Modeling

arXiv:2606.23436v1 Announce Type: new Abstract: Unsupervised video object tracking aims to decompose dynamic scenes into persistent, object-centric entities without manual annotations. Many recent app

Tutorials

Rethinking Prototype-based Similarity Learning for Few-Shot Object Detection

arXiv:2606.23069v1 Announce Type: new Abstract: Few-shot object detection aims to detect novel object categories from only a few labeled examples, avoiding costly large-scale annotation. Recent protot

tutorialsarxiv-cs-cv

Rethinking the Adaptation of Vision Foundation Models for Efficient Cell Segmentation

arXiv:2606.21913v1 Announce Type: new Abstract: Cell segmentation is critical for computational pathology and biomedical discovery. While recent Vision Foundation Models (VFMs) have demonstrated remar

Retrieval-Augmented Anatomical Guidance for Text-to-CT Generation

arXiv:2603.08305v2 Announce Type: replace Abstract: Text-conditioned generative models for volumetric medical imaging provide semantic control but lack explicit anatomical guidance, often resulting in

Retrieval-Augmented Multimodal Learning for Enzyme-Substrate Interaction Prediction Under Low-Homology Shift

arXiv:2606.22823v1 Announce Type: new Abstract: Enzyme substrate interaction (ESI) prediction is a fundamental computational task for biocatalyst discovery and reaction screening in large biochemical

Revealing the Pitfalls and Re-Evaluating the Advancement of Heterophilic Graph Learning

arXiv:2409.05755v3 Announce Type: replace Abstract: Over the past decade, Graph Neural Networks (GNNs) have achieved great success on machine learning tasks with relational data. However, recent studi

Revisiting OmniAnomaly for Anomaly Detection: performance metrics and comparison with PCA-based models

arXiv:2603.18985v2 Announce Type: replace-cross Abstract: Deep learning models have become the dominant approach for multivariate time series anomaly detection (MTSAD), often reporting substantial per

Revisiting the Neural Tangent Kernel: the role of large width and depth

arXiv:2511.07272v2 Announce Type: replace Abstract: Overparameterized fully-connected neural networks have been shown to behave like kernel models when trained with gradient descent, assuming standard

Reward-free Pretraining for Reinforcement Learning via Occupancy Coverage Maximization

arXiv:2606.21271v1 Announce Type: new Abstract: Sparse rewards pose a central challenge in reinforcement learning, since agents receive no informative signal until they reach their goal. Intrinsic-rew

Right Knowledge, Wrong Answer: Test-Time Steering for Temporal Fact Conflicts in Open-Weight Language Models

arXiv:2606.20959v1 Announce Type: new Abstract: Large language models can store both outdated facts and newer superseding facts in their parameters, but standard prompting may still elicit the outdate

Local Ai

RIZZ: Routing Interactions to Near Zero-Interference Zones for Continual Adaptation of Black-Box Agents

arXiv:2606.20638v1 Announce Type: cross Abstract: Large language models are increasingly deployed as long-lived agents that must adapt across users, tasks, domains, modalities, and feedback regimes wi

local-aiarxiv-cs-lg

RLM-Cascade: Response-Level Speculative Decoding for Cost-Efficient LLM API Serving

arXiv:2606.22840v1 Announce Type: new Abstract: We present RLM-Cascade, a proxy-layer system that applies speculative decoding at the response level to reduce LLM API costs without requiring model arc

RoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations

arXiv:2606.22142v1 Announce Type: new Abstract: We present RoboLineage, an agent-native data lifecycle governance system for robot policy iteration. Modern robot policies improve through repeated data

Robot Critics that Sweat the Small Stuff

arXiv:2606.21572v1 Announce Type: new Abstract: Large vision-language models contain several priors about the world and object interactions, making them useful critics during inference to steer robot

Robot Self-Improvement via Human-Video Dynamics Models

arXiv:2606.21406v1 Announce Type: cross Abstract: A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, a

Robust 3DGS-based SLAM via Adaptive Kernel Smoothing

model-releasesarxiv-cs-cv

arXiv:2511.23221v2 Announce Type: replace Abstract: In this paper, we challenge the conventional notion in 3DGS-SLAM that rendering quality is the primary determinant of tracking accuracy. We argue th

Robust and Differentially Private Principal Component Analysis

arXiv:2507.15232v2 Announce Type: replace-cross Abstract: Recent advances have sparked significant interest in the development of privacy-preserving Principal Component Analysis (PCA). However, many e

Robust Auto-associative Memory via Convolutional Restricted Hopfield Networks

arXiv:2606.20666v1 Announce Type: cross Abstract: Associative memory models play a fundamental role in pattern retrieval, but their performance often degrades under adversarial perturbations and sever

Robust Diffusion Models via Divergence-Induced Weighted Denoising

arXiv:2606.22521v1 Announce Type: cross Abstract: We show that replacing the standard MSE denoising loss in diffusion models with a nonlinear transformation induced by an f-divergence yields a simple

Robust Image-Driven Phenotyping of Ovarian Tumor Cells using Optimized Dynamic Features in Hyperbolic Channels

arXiv:2606.20703v1 Announce Type: new Abstract: Label-free, image-based cellular mechanophenotyping in microfluidic devices provides a high-throughput method for single-cell profiling. However, while

Robust Representation Learning in Masked Autoencoders

arXiv:2602.03531v2 Announce Type: replace-cross Abstract: Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the internal representations they learn remain le

Agents

Robust Tightly-Coupled Filter-Based Monocular Visual-Inertial State Estimation and Graph-Based Evaluation for Autonomous Drone Racing

arXiv:2603.02742v2 Announce Type: replace Abstract: Autonomous drone racing (ADR) demands state estimation that is simultaneously computationally efficient and resilient to the perceptual degradation

agentsarxiv-cs-ro

Applications

Robust Zero-Shot Generalization for Open-Vocabulary Action Recognition via Task Arithmetic

arXiv:2606.20734v1 Announce Type: new Abstract: Open Vocabulary Action Recognition (OVAR) enables the recognition of novel actions by leveraging vision-language representations, overcoming the limitat

applicationsarxiv-cs-cv

Robustness Cannot be Reduced to Regularization: Studying Adversarial Training Beyond the Linear Case

arXiv:2606.21488v1 Announce Type: new Abstract: The vulnerability of ML models to adversarial examples has recently emerged as a major concern. While adversarial training is one of the most effective