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Beyond Point-Attached Semantics: Object-Centric Semantic Fields for Generalizable Manipulation

arXiv:2607.03163v1 Announce Type: new Abstract: Generalizable robot manipulation requires stable 3D understanding of functional object parts, such as handles, tool heads, openings, and graspable regio

safetyarxiv-cs-ro

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Research

Beyond Post-Quantization: Native Hash Learning with a Dedicated HASH Token

DGX agent

arXiv:2607.03328v1 Announce Type: new Abstract: Efficient large-scale image retrieval requires compact representations that preserve semantic similarity under fast Hamming-space search. Deep hashing i

researcharxiv-cs-cv

7 Jul 2026

Beyond Random Sampling: Distribution-Aware Alignment for Semi-Supervised Medical Image Segmentation

arXiv:2607.04249v1 Announce Type: new Abstract: Precise medical image segmentation is crucial for clinical diagnosis and treatment planning, yet relies heavily on expensive expert annotations. Semi-su

safetyarxiv-cs-cv

Beyond Satisfaction: Learning Associations Between Content, Reviews, and Well-Being

arXiv:2607.02539v1 Announce Type: cross Abstract: Digital platforms commonly optimize for satisfaction using signals such as ratings, likes, and sentiment, implicitly treating satisfaction as a proxy

Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus

model-releasesarxiv-cs-cv

arXiv:2607.04149v1 Announce Type: new Abstract: In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language M

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL

arXiv:2607.03833v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved remarkable success in Text-to-SQL tasks, their deployment in real-world environments is hindered by l

Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents

model-releasesarxiv-cs-ai

arXiv:2604.00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and

Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning

arXiv:2607.04577v1 Announce Type: new Abstract: Code models strictly prioritize functional correctness, leaving software energy efficiency as an unoptimized byproduct. Training models to generate ener

applicationsarxiv-cs-lg

Beyond travel mode: urban context shapes active mobility's mental health effects over time

arXiv:2607.04520v1 Announce Type: new Abstract: Active mobility is widely promoted for sustainable and healthier living, but whether it translates into equitable mental health benefits across individu

Tutorials

Binary Iterative Method for Non-targeted Adversarial Attack

arXiv:2607.04145v1 Announce Type: cross Abstract: Adversarial attacks guide and provide additional training and test data for both adversarial training and adversarial robustness validation, and expos

tutorialsarxiv-cs-cv

Agents

Biological Motifs for Agentic Control

arXiv:2607.04240v1 Announce Type: new Abstract: The transition of Large Language Models (LLMs) from passive generators to autonomous agents has introduced significant challenges in reliability, securi

agentsarxiv-cs-ai

Biologically Informed Deep Neural Networks for Multi-Omic Integration, Pathway Activity Inference and Risk Stratification in Cancer

arXiv:2607.05306v1 Announce Type: new Abstract: Integrating complex, multi-omics data presents significant challenges. Existing approaches often face a trade-off between model interpretability and rep

Biomechanics-aware Multi-view Markerless Motion Capture of Dexterous Hand Movements

arXiv:2607.02796v1 Announce Type: new Abstract: Markerless motion capture (MMC) techniques have been widely beneficial in biomechanical analysis of human movement; however, application to complex moti

BiSLW: Bi-Spectral Latent Watermarking for Generative Diffusion Models

arXiv:2607.02643v1 Announce Type: new Abstract: Diffusion-based generative models have transformed visual content synthesis, yet they remain vulnerable to unauthorized usage and lack reliable attribut

safetyarxiv-cs-cv

Boosting Automatic Exercise Evaluation Through Musculoskeletal Simulation-Based IMU Data Augmentation

arXiv:2505.24415v2 Announce Type: replace-cross Abstract: Automated evaluation of movement quality can enhance physiotherapeutic treatment and sports training by providing objective, real-time feedbac

Bootstrap Flow-Map Tree Sampling Enables Online Feedback Driven Search

arXiv:2607.02915v1 Announce Type: cross Abstract: In many scientific and engineering domains, maximizing discovery within a limited sampling budget demands strategic, observation-guided exploration. W

BoRP: Bootstrapped Regression Probing for Scalable and Human-Aligned LLM Evaluation

arXiv:2601.18253v2 Announce Type: replace-cross Abstract: Accurate evaluation of user satisfaction is critical for iterative development of conversational AI. However, for open-ended assistants, tradi

Boundary-layer asymptotics for Gaussian-smoothed singular measures

model-releasesarxiv-cs-lg

arXiv:2607.04514v1 Announce Type: cross Abstract: We study the small-noise asymptotics of Euclidean heat regularizations of probability measures supported on manifolds with corners. Near a boundary or

BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNet

arXiv:2511.12853v2 Announce Type: replace-cross Abstract: Brain tumors induce complex structural deformations that obscure the patient' s original neuroanatomy, making it difficult to distinguish tumo

Brand-as-Memory: Vision-Language Models Encode Causal, Mechanistically Localizable Credibility Priors for News Sources

model-releasesarxiv-cs-ai

arXiv:2607.03365v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly read news and web content as images, where the publisher's identity is visually present. We show that VLMs

Breaking the One-Dimensional Expressibility-Trainability Tradeoff

model-releasesarxiv-cs-lg

arXiv:2607.04598v1 Announce Type: cross Abstract: Expressive parameterized quantum circuits (PQCs) are often designed under a dilemma: the growth of expressibility and entangling power (EP) that impro

Bridging Interleaved Multi-Modal Reasoning as a Unified Decision Process

arXiv:2607.03748v1 Announce Type: new Abstract: Unified multi-modal models (UMMs) have shown promising interleaved text-image reasoning capabilities, yet effectively optimizing such multi-turn generat

Agents

Builder, Defender, Breaker: The Case Against Removing the Human from the AI-Driven Security Lifecycle

arXiv:2607.03215v1 Announce Type: cross Abstract: Artificial intelligence has spread across the whole of the security lifecycle. The same family of models now writes application code, hardens it, and

agentsarxiv-cs-ai

BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception

arXiv:2607.03184v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive general capabilities, they struggle with fine-grained perception in ultra-high-res

Tutorials

C^3ASD: Multi-Level Consistency-Driven Representation Learning

arXiv:2607.03018v1 Announce Type: new Abstract: Active Speaker Detection determines whether a visible person in a video is speaking at each moment. While recent audio-visual fusion methods perform wel

tutorialsarxiv-cs-cv

CABTO: Context-Aware Behavior Tree Grounding for Robot Manipulation

arXiv:2603.16809v2 Announce Type: replace-cross Abstract: Behavior Trees (BTs) offer a powerful paradigm for designing modular and reactive robot controllers. BT planning, an emerging field, provides

researcharxiv-cs-ai

CAC-VLA: Context-Gated Action Conditioning for Vision-Language-Action Models

arXiv:2607.04816v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a promising paradigm for generalist robot manipulation, where visual-language representations are used t

researcharxiv-cs-ro

CAGE-1: Control, Assurance, and Governance Evaluation for Enterprise Agentic AI

arXiv:2607.03510v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from experimentation into operational workflows. Early programs focused on model access and retrieval-aug

Can Conversational Temporal Dynamics Improve Depression Detection in Dyads? A Preliminary Investigation in Multi-Modality Perspectives

arXiv:2607.03744v1 Announce Type: new Abstract: Automatic depression detection from clinical interviews typically models the semantic content and acoustic characteristics of participant speech. Howeve

researcharxiv-cs-ai

Can Dialects Be Steered Like Languages? Sparse Neurons and Distributed Directions in Arabic LLMs

arXiv:2607.03936v1 Announce Type: new Abstract: A key challenge in Arabic NLP is the scarcity of dialectal data relative to Modern Standard Arabic (MSA), causing LLMs to overproduce MSA and struggle w

Local Ai

Can Model Merging Improve Aggregation in DiLoCo?

arXiv:2607.03011v1 Announce Type: cross Abstract: Model merging techniques, which aggregate independently finetuned models into one to combine their capabilities, have become a topic of significant in

local-aiarxiv-cs-ai

Can temporal article-level credibility signals improve domain-level credibility prediction?

arXiv:2607.04560v1 Announce Type: new Abstract: Web domain credibility evaluation is vital for combating misinformation. It is conducted by examining factors such as domain type, transparency, and ove

safetyarxiv-cs-cl

Cancelable Biometric Template Protection Based on Multi-Instance Fusion: A Contralateral Iris Approach

arXiv:2607.02860v1 Announce Type: new Abstract: Biometric templates are vulnerable to theft if stored without protection. Unlike passwords, a compromised iris cannot be reissued. Although existing can

Candidate-Constrained Retrieval-Augmented Generation for LongEval-RAG: System Design and Empirical Analysis

arXiv:2607.04008v1 Announce Type: new Abstract: We present a candidate-constrained retrieval-augmented generation system for LongEval-RAG, where each query is associated with an organizer-provided can

CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

arXiv:2607.05242v1 Announce Type: cross Abstract: Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). Ho

Tutorials

Canonical quantization of neurons

arXiv:2607.05000v1 Announce Type: cross Abstract: Canonical quantization provides a systematic procedure for constructing quantum models from classical Hamiltonians. Here, we apply this principle to a

tutorialsarxiv-cs-lg

CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning

arXiv:2607.04619v1 Announce Type: cross Abstract: Modern automated audio captioning systems pair a frozen audio encoder with a large language model (LLM) via a trainable projector, incurring the encod

CaresAI at SMM4H-HeaRD 2026: Predicting TNM Staging

arXiv:2607.03466v1 Announce Type: cross Abstract: This study aims to predict Tumor, Node, and Metastasis (TNM) stage labels independently, with the Cancer Genome Atlas (TCGA) pathology report as the s

CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs

arXiv:2607.04854v1 Announce Type: new Abstract: Despite their strong reasoning capabilities and extensive world knowledge, Large Language Models (LLMs) frequently generate plans that violate task cons

CaSPECT: Discovering Causally Homogeneous Subgroups via Directed Spectral Clustering

arXiv:2607.03364v1 Announce Type: cross Abstract: We propose extbf{CaSPECT}, a causal spectral clustering framework for discovering causally homogeneous subgroups from observational data. Rather than

Causal ASCEND: Scalable Two-tier Causal Discovery on High Dimensional Multi-omics Data

arXiv:2607.04527v1 Announce Type: cross Abstract: Biological systems exhibit a hierarchical structure, characterised by directed flow from upstream regulators to downstream effects. Although this orde

Causal Mechanism Reduction: Mechanism Replacement for Neural Network Pruning and Abstraction

arXiv:2602.24266v2 Announce Type: replace-cross Abstract: Which internal mechanisms of a neural network can be replaced while preserving the computation it performs? Structured pruning asks for smalle

Local Ai

Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy

arXiv:2607.05204v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade im

local-aiarxiv-cs-cv

CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes

arXiv:2404.01299v3 Announce Type: replace-cross Abstract: Causal video question answering (QA) has garnered increasing interest, yet existing datasets often lack depth in causal reasoning. To address

researcharxiv-cs-ai

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games

model-releasesarxiv-cs-ai

arXiv:2607.04293v1 Announce Type: cross Abstract: Building AI Scientist agents with Large Language Models (LLMs) has recently attracted growing attention. Since scientific discovery fundamentally reli

CCFM: Collision-Constrained Flow Matching for Safety-Critical Scenario Generation

arXiv:2607.04451v1 Announce Type: new Abstract: Evaluation of autonomous vehicle (AV) planners in safety-critical closed-loop simulation is essential for real-world deployment. However, generating con

safetyarxiv-cs-cv

CDCP: Conditional Diffusion Model with Contextual Prompts for Multi-task Offline Safe Reinforcement Learning

arXiv:2607.03903v1 Announce Type: new Abstract: Multi-task offline safe reinforcement learning (RL) promises to learn a shared optimal safe policy from offline data across multiple tasks. This paradig

safetyarxiv-cs-lg

CDST: Color Disentangled Style Transfer for Universal Style Reference Customization

arXiv:2506.13770v2 Announce Type: replace Abstract: We introduce Color Disentangled Style Transfer (CDST), a novel and efficient two-stream style transfer training paradigm which completely isolates c