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Bayesian three-dimensional seismic travel-time tomography for active- and passive-source seismic data using physics-informed neural network

arXiv:2606.21789v1 Announce Type: cross Abstract: Accurate 3D seismic velocity modeling through seismic travel-time tomography using both active- and passive-source data provides critical underpinning

applicationsarxiv-cs-lg

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Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models

DGX agent

arXiv:2606.21645v1 Announce Type: cross Abstract: Large language models (LLMs) can readily reproduce conventional expressions, yet their ability to model gradient frequency distributions remains under

safetyarxiv-cs-lg

23 Jun 2026

BELDE: Building a Large-scale Earth-observation Land-cover Dataset for Europe

arXiv:2606.20909v1 Announce Type: new Abstract: Earth observation imagery plays a critical role in environmental monitoring, urban planning, disaster assessment, and climate analysis. While multi-spec

BELLS-O: Evaluating the Operational Trade-offs of LLM Supervision Systems

arXiv:2606.20668v1 Announce Type: cross Abstract: LLM supervision systems, namely input/output moderation filters and jailbreak detectors, are the primary safeguard against misuse in deployed AI appli

Benchmarking Robot Memory Under Interference

arXiv:2606.22338v1 Announce Type: cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment. The robot's tasks may often req

Benchmarking Vision-Language Models for Microscopic Plant Image Understanding

arXiv:2606.22497v1 Announce Type: new Abstract: Microscopic imaging provides essential visual evidence for studying plant biology and pathology at the cellular and subcellular levels. However, existin

Betting on Moments: Legendre Jumper Martingales for Online Exchangeability Testing

arXiv:2606.20859v1 Announce Type: cross Abstract: We present a family of conformal test martingales based on shifted Legendre polynomials, which extends the Simple Jumper martingale. The Simple Legend

applicationsarxiv-cs-lg

BEV-Denoise: Learning Intrinsic Noise for Accurate Bird's-Eye-View Semantic Segmentation

arXiv:2606.22931v1 Announce Type: new Abstract: In this paper, we present a framework dubbed extbf{BEV-Denoise} that estimates and removes intrinsic noise from learned Bird's-Eye-View (BEV) features t

applicationsarxiv-cs-cv

Beyond a Single Light: A Large-Scale Aerial Dataset for Urban Scene Reconstruction Under Varying Illumination

arXiv:2512.14200v2 Announce Type: replace Abstract: Recent advances in Neural Radiance Fields and 3D Gaussian Splatting have demonstrated strong potential for large-scale UAV-based 3D reconstruction t

applicationsarxiv-cs-cv

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

arXiv:2606.15127v2 Announce Type: replace Abstract: Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students inte

Beyond Damage Assessment: Recyclable Material Detection in Aerial Disaster Imagery Using a Lightweight Patch-Based Framework

arXiv:2606.21279v1 Announce Type: new Abstract: Nowadays, more and more disasters of different natures are appearing. Several disaster assessment approaches have been developed in order to identify da

Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategies

arXiv:2606.20599v1 Announce Type: cross Abstract: Tree of Thought (ToT) search has become a promising direction for improving the reasoning capabilities of large language models, but deploying these m

Beyond Flat Labels: Level-Restricted Contrastive Learning for Hierarchical Fine-Grained Vision Classification

arXiv:2606.21838v1 Announce Type: new Abstract: Multimodal contrastive learning has enabled zero-shot visual classification by aligning images with textual categories. However, in hierarchically struc

Beyond Importance: Interchange-Sobol Sensitivity Reveals Task-Specific Content Channels in Transformer Components

arXiv:2606.20678v1 Announce Type: cross Abstract: Mechanistic interpretability methods summarize a transformer component by a single importance score, conflating two distinct roles: a component may ma

Beyond 'One Language, One Script': Quantifying Orthographic Bias in Multilingual VLMs with PuMVR

arXiv:2606.20770v1 Announce Type: cross Abstract: Current Vision-Language Models (VLMs) are celebrated for their multilingual capabilities, yet they operate under a flawed assumption: that one languag

Beyond ROC-AUC: Operating-Point Performance Reporting for Biometric Verification

arXiv:2606.20680v1 Announce Type: new Abstract: A biometric verifier is often deployed with a strict false match budget, so only a narrow, low false match rate (FMR) slice of the score range is used.

Tutorials

Beyond Templates: Revisiting Zero-Shot Remote Sensing through Meta-Prompting

arXiv:2606.20702v1 Announce Type: new Abstract: Vision-language models (VLMs) have sparked growing interest in zero-shot Earth Observation (EO) downstream tasks, with further gains enabled by remote-s

tutorialsarxiv-cs-cv

Beyond the LUMIR challenge: The pathway to foundational registration models

arXiv:2505.24160v3 Announce Type: replace-cross Abstract: Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benc

Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning

arXiv:2606.21775v1 Announce Type: new Abstract: Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environme

Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning

arXiv:2606.22171v1 Announce Type: new Abstract: Epidemic forecasting models typically rely on surveillance data reported over administrative regions, treating them as atomic units, thereby obscuring s

applicationsarxiv-cs-lg

B[FM]^2: Brain Foundation Model via Flow Matching with SplitUNet

arXiv:2606.20812v1 Announce Type: new Abstract: EEG foundation models can learn generalizable representations from large-scale EEG corpora to enable single-backbone transfer across diverse clinical an

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation

arXiv:2511.22973v2 Announce Type: replace Abstract: Long video generation is a critical step toward building realistic world models, requiring both high visual fidelity and long-range interaction cons

BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation

arXiv:2606.23531v1 Announce Type: new Abstract: Endoscopic retrograde cholangiopancreatography (ERCP) demands precise endoscopic navigation and stable biliary cannulation within a narrow monocular fie

safetyarxiv-cs-ro

Biological Sex Determination in Cadavers Using Deep Learning Algorithms from Computed Tomography Images of Pelvis and Skull

arXiv:2606.22515v1 Announce Type: new Abstract: Sexual identification of decomposed cadavers challenges traditional methods dependent on visual anthropological analysis. This study evaluates state-of-

BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language

arXiv:2606.22138v1 Announce Type: cross Abstract: We present BioMatrix, the first multimodal foundation model that natively integrates sequences, structures, and natural language for both molecules an

BIT-Nav: Brain-Inspired Trajectory Memory for Embodied Navigation

arXiv:2606.21398v1 Announce Type: new Abstract: Vision-Language Models (VLMs) for embodied navigation rely on selecting a fixed number of frames from a growing trajectory history. As episodes extend,

Black-Box Continual Learning for Vision-Language Models

arXiv:2606.22999v1 Announce Type: new Abstract: The rapid deployment of Vision-Language Models (VLMs) in dynamic environments necessitates the ability to learn continuously without forgetting. However

BLENDS: Bayesian Learning-Enhanced Deep Smoothing for GNSS-Denied Environments

arXiv:2606.22456v1 Announce Type: new Abstract: Maintaining accurate navigation during GNSS outages remains a significant challenge for autonomous systems relying on low-cost inertial sensors. While c

safetyarxiv-cs-ro

Boosting CVaR Policy Optimization with Quantile Gradients

arXiv:2601.22100v3 Announce Type: replace Abstract: Optimizing Conditional Value-at-risk (CVaR) using policy gradient (a.k.a CVaR-PG) faces significant challenges of sample inefficiency. This ineffici

Boosting Neural Video Codec via Scale-Driven Online Flow Refinement

arXiv:2606.23023v1 Announce Type: new Abstract: Although state-of-the-art neural video codecs (NVCs) have achieved remarkable performance, they suffer from limited generalization when encountering com

Boundary-by-Mask: Few-Shot Instance Segmentation with Mask-Conditioned Boundary Learning for Texture-Poor Industrial Parts

arXiv:2606.21594v1 Announce Type: new Abstract: Recent advances in large pre-trained models have led to remarkable progress in instance segmentation on general images. However, industrial scenarios re

Tutorials

BoxCtrl: 3D-Aware Visual Prompting for Geometric Image Editing

arXiv:2606.23270v1 Announce Type: new Abstract: As instruction-based editing models and multimodal large language models advance, diverse image editing tasks have become feasible. However, achieving p

tutorialsarxiv-cs-cv

Bracing for Impact: Robust Humanoid Push Recovery and Locomotion with Reduced Order Models

arXiv:2505.11495v2 Announce Type: replace Abstract: Push recovery during locomotion will facilitate the deployment of humanoid robots in human-centered environments. In this paper, we present a unifie

Brain-Adapter: A Dual-Stream Vision-Language MIL Framework for Comprehensive 3D CT Diagnosis of Acute Intracranial Pathologies

arXiv:2606.23494v1 Announce Type: new Abstract: Automated diagnosis of 3D brain CT scans is essential for critical care, yet it remains challenging due to the heavy reliance on manual annotations and

Tutorials

Brain-Inspired Stochastic Joint Embedding Representation Learning

arXiv:2505.11129v2 Announce Type: replace Abstract: Representation learning is one of the key research topics in machine learning, and the framework of self-supervised learning (SSL) has revolutionize

tutorialsarxiv-cs-cv

BranchShine: Compact Raw-Audio-to-IPA Transcription with a RoPE E-Branchformer Encoder

arXiv:2606.22824v1 Announce Type: new Abstract: Speech-to-IPA transcription is useful when the desired output is pronunciation rather than orthographic text, but competitive multilingual systems are o

Local Ai

Breaking chains with trees: Deep learning with O(log N) parallel time complexity

arXiv:2606.21497v1 Announce Type: new Abstract: Modern deep neural network architectures are trained via backpropagation, which requires errors to be sequentially propagated through all layers before

local-aiarxiv-cs-lg

Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning

arXiv:2606.23199v1 Announce Type: new Abstract: Attributed graph clustering partitions nodes by jointly exploiting node attributes and graph topology. It remains challenging due to attribute heterogen

Bridging Multi-Valued Heuristics and Dimensionality Reduction in Multi-Objective Search

arXiv:2606.20644v1 Announce Type: cross Abstract: Multi-objective shortest-path (MOSP) algorithms traditionally rely on single-valued heuristics (SVHs), which associate each state with a single admiss

Bridging Semantics and Kinematics: A Modular Framework for Zero-Shot Robotic Manipulation

arXiv:2606.23157v1 Announce Type: new Abstract: This paper presents a modular training-free framework for zero-shot, language-guided robotic manipulation in semi-structured environments. The architect

Bridging Single Distortion Artifacts and Multifactorial Clinical Quality: Few-shot Biparametric MRI Quality Assessment via Distortion-trained Prototypical Networks

arXiv:2606.18872v2 Announce Type: replace Abstract: Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by

applicationsarxiv-cs-cv

Local Ai

Build Once, Monitor Continuously: Persistent Semantic Mapping via Autonomous Exploration and Open-Vocabulary Object Updates

arXiv:2409.15493v4 Announce Type: replace-cross Abstract: Persistent semantic monitoring of indoor spaces such as warehouses, hospitals, and offices requires a robot to repeatedly monitor an environme

local-aiarxiv-cs-cv

Bypassing Minimization Bias: A Shift-Invariant Variance Estimator for Off-Equilibrium Local Learning Coefficients

arXiv:2606.22389v1 Announce Type: new Abstract: Singular Learning Theory leverages the Local Learning Coefficient (LLC) to quantify the geometry of neural network loss landscapes. However, mean-energy

C^2GR: Coupled Comprehensive Generative Replay for a Continually Learnable Universal Segmentation Model

arXiv:2606.23473v1 Announce Type: new Abstract: Universal segmentation models exhibit significant potential for diverse tasks involving different imaging modalities and segmentation objectives. Task-I

Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning

arXiv:2606.16214v3 Announce Type: replace Abstract: Modern deep learning models remain notoriously prone to overconfidence, limiting their reliability in high-stakes applications. Bayesian methods aim

Can LLMs Control Readability? A Multi-Dimensional Evaluation Framework for CEFR-Controlled Arabic Generation

arXiv:2606.21981v1 Announce Type: cross Abstract: While Large Language Models (LLMs) can generate fluent Arabic text, their ability to reliably control readability levels remains unclear. We propose a

Can Reasoning Models Detect Changes to their Chains of Thought?

arXiv:2606.22085v1 Announce Type: cross Abstract: There are many reasons one may want to edit a model's chain of thought (CoT) -- e.g., to prefill it with reasoning from a stronger model or to remove

Can Single-View Mesh Reconstruction Generalize to Robot Camera Rotation?

arXiv:2606.22987v1 Announce Type: new Abstract: Single-view mesh reconstruction predicts object meshes and spatial layouts from a single observation, making it attractive for fast robot spatial reason