Search: “framework”

UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception

arXiv:2604.14089v1 Announce Type: new Abstract: We present UMI-3D, a multimodal extension of the Universal Manipulation Interface (UMI) for robust and scalable data collection in embodied manipulation

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UNBOX: Unveiling Black-box visual models with Natural-language

DGX agent

arXiv:2603.08639v2 Announce Type: replace Abstract: Ensuring trustworthiness in open-world visual recognition requires models that are interpretable, fair, and robust to distribution shifts. Yet moder

safetyarxiv-cs-cv

16 Apr 2026

UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization

arXiv:2604.13383v1 Announce Type: new Abstract: Ambient Lighting Normalization (ALN) aims to restore images degraded by complex, spatially varying illumination conditions. Existing methods, such as IF

UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes

arXiv:2511.23332v2 Announce Type: replace Abstract: Instruction-driven segmentation in remote sensing generates masks from guidance, offering great potential for accessible and generalizable applicati

Local Ai

V2V With Audio File Lipsync?

local-air-stablediffusion

This r/StableDiffusion post likely discusses how to perform video-to-video (V2V) generation with audio-driven lip synchronization, a workflow where an existing video is transformed so that a subject's

VGGT-Segmentor: Geometry-Enhanced Cross-View Segmentation

arXiv:2604.13596v1 Announce Type: new Abstract: Instance-level object segmentation across disparate egocentric and exocentric views is a fundamental challenge in visual understanding, critical for app

VRAG-DFD: Verifiable Retrieval-Augmentation for MLLM-based Deepfake Detection

arXiv:2604.13660v1 Announce Type: new Abstract: In Deepfake Detection (DFD) tasks, researchers proposed two types of MLLM-based methods: complementary combination with small DFD detectors, or static f

safetyarxiv-cs-cv

Local Ai

Weakly-supervised Learning for Physics-informed Neural Motion Planning via Sparse Roadmap

arXiv:2604.13204v1 Announce Type: new Abstract: The motion planning problem requires finding a collision-free path between start and goal configurations in high-dimensional, cluttered spaces. Recent l

local-aiarxiv-cs-ro

What Are We Really Measuring? Rethinking Dataset Bias in Web-Scale Natural Image Collections via Unsupervised Semantic Clustering

arXiv:2604.13610v1 Announce Type: new Abstract: In computer vision, a prevailing method for quantifying dataset bias is to train a model to distinguish between datasets. High classification accuracy i

safetyarxiv-cs-cv

Tutorials

X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations

arXiv:2511.04671v2 Announce Type: replace-cross Abstract: Human videos are a scalable source of training data for robot learning. However, humans and robots significantly differ in embodiment, making

tutorialsarxiv-cs-cv

ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs

arXiv:2512.09953v2 Announce Type: replace-cross Abstract: Machine unlearning aims to remove the influence of specific data points from a trained model to satisfy privacy, copyright, and safety require

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3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope

arXiv:2604.12027v1 Announce Type: new Abstract: Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg informat

researcharxiv-cs-ro

5/5 The takeaway: If your agent relies on an LLM judge for selection accuracy, measuring code quality isn’t enough; you need a measure of th…

5/5 The takeaway: If your agent relies on an LLM judge for selection accuracy, measuring code quality isn’t enough; you need a measure of the model's inductive bias toward the 'fingerprint' of a gold

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A Comparison of Reinforcement Learning and Optimal Control Methods for Path Planning

arXiv:2604.12628v1 Announce Type: cross Abstract: Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge. While traditional optimal control methods can find idea

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A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results

arXiv:2407.17182v4 Announce Type: replace Abstract: In this work, we consider the non-invasive medical imaging modality of Electrical Impedance Tomography (EIT), where the goal is to recover the condu

researcharxiv-cs-lg

A document is worth a structured record: Principled inductive bias design for document recognition

arXiv:2507.08458v2 Announce Type: replace-cross Abstract: Many document types use intrinsic, convention-driven structures that serve to encode precise and structured information, such as the conventio

A Multi-Agent Feedback System for Detecting and Describing News Events in Satellite Imagery

arXiv:2604.12772v1 Announce Type: new Abstract: Changes in satellite imagery often occur over multiple time steps. Despite the emergence of bi-temporal change captioning datasets, there is a lack of m

agentsarxiv-cs-cv

A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning

arXiv:2603.08291v3 Announce Type: replace Abstract: Multimodal Mathematical Reasoning (MMR) has recently attracted increasing attention for its capability to solve mathematical problems involving both

A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)

arXiv:2604.11944v1 Announce Type: new Abstract: Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series d

researcharxiv-cs-lg

ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

model-releasesarxiv-cs-cl

arXiv:2602.11236v2 Announce Type: replace-cross Abstract: Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, man

Active Imitation Learning for Thermal- and Kernel-Aware LFM Inference on 3D S-NUCA Many-Cores

arXiv:2604.11948v1 Announce Type: new Abstract: Large Foundation Model (LFM) inference is both memory- and compute-intensive, traditionally relying on GPUs. However, the limited availability and high

safetyarxiv-cs-lg

Actuation space reduction to facilitate insightful shape matching in a novel reconfigurable tendon driven continuum manipulator

arXiv:2604.12792v1 Announce Type: new Abstract: In tendon driven continuum manipulators (TDCMs), reconfiguring the tendon routing enables tailored spatial deformation of the backbone. This work presen

researcharxiv-cs-ro

Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks

arXiv:2604.12945v1 Announce Type: cross Abstract: Deep neural networks are typically trained by uniformly sampling large datasets across epochs, despite evidence that not all samples contribute equall

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat

researcharxiv-cs-ai

Adaptive Test-Time Scaling for Zero-Shot Respiratory Audio Classification

arXiv:2604.12647v1 Announce Type: cross Abstract: Automated respiratory audio analysis promises scalable, non-invasive disease screening, yet progress is limited by scarce labeled data and costly expe

researcharxiv-cs-cl

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning

arXiv:2505.17086v4 Announce Type: replace Abstract: Large Language Models (LLMs) equipped with modern Retrieval-Augmented Generation (RAG) systems often employ multi-turn interaction pipelines to inte

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Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

arXiv:2604.12129v1 Announce Type: new Abstract: The transition from stateless model inference to stateful agentic execution is reshaping the systems assumptions underlying modern AI infrastructure. Wh

agentsarxiv-cs-ai

AffectAgent: Collaborative Multi-Agent Reasoning for Retrieval-Augmented Multimodal Emotion Recognition

arXiv:2604.12735v1 Announce Type: new Abstract: LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this p

Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors

arXiv:2604.11957v1 Announce Type: cross Abstract: Self-driving laboratories promise to accelerate materials discovery. Yet current automated solid-state synthesis platforms are limited to ambient cond

agentsarxiv-cs-lg

AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text Generation

arXiv:2604.06812v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucinati

researcharxiv-cs-cl

Applications

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding

arXiv:2604.12335v1 Announce Type: new Abstract: Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object coun

applicationsarxiv-cs-cv

AnyPoC: Universal Proof-of-Concept Test Generation for Scalable LLM-Based Bug Detection

model-releasesarxiv-cs-ai

arXiv:2604.11950v1 Announce Type: cross Abstract: While recent LLM-based agents can identify many candidate bugs in source code, their reports remain static hypotheses that require manual validation,

Are Video Reasoning Models Ready to Go Outside?

model-releasesarxiv-cs-ai

arXiv:2603.10652v2 Announce Type: replace-cross Abstract: In real-world deployment, vision-language models often encounter disturbances such as weather, occlusion, and camera motion. Under such condit

ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception

arXiv:2604.12255v1 Announce Type: cross Abstract: Dynamic facial expression recognition in the wild remains challenging due to data scarcity and long-tail distributions, which hinder models from effec

ART-VITON: Measurement-Guided Latent Diffusion for Artifact-Free Virtual Try-On

arXiv:2509.25749v2 Announce Type: cross Abstract: Virtual try-on (VITON) aims to generate realistic images of a person wearing a target garment, requiring precise garment alignment in try-on regions a

Applications

ArtifactWorld: Scaling 3D Gaussian Splatting Artifact Restoration via Video Generation Models

arXiv:2604.12251v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) delivers high-fidelity real-time rendering but suffers from geometric and photometric degradations under sparse-view constr

applicationsarxiv-cs-cv

ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack

arXiv:2509.25843v2 Announce Type: replace Abstract: Large language models (LLMs), despite being safety-aligned, exhibit brittle refusal behaviors that can be circumvented by simple linguistic changes.

ASTRA: Let Arbitrary Subjects Transform in Video Editing

arXiv:2510.01186v2 Announce Type: replace Abstract: While existing video editing methods excel with single subjects, they struggle in dense, multi-subject scenes, frequently suffering from attention d

BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH

arXiv:2604.12005v1 Announce Type: cross Abstract: Bayesian optimization (BO) has for sequential optimization of expensive black-box functions demonstrated practicality and effectiveness in many real-w

Beyond Factual Grounding: The Case for Opinion-Aware Retrieval-Augmented Generation

arXiv:2604.12138v1 Announce Type: new Abstract: RAG systems have transformed how LLMs access external knowledge, but we find that current implementations exhibit a bias toward factual, objective conte

Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score

arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin

agentsarxiv-cs-cl

Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage

model-releasesarxiv-cs-ai

arXiv:2603.08819v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems combine document retrieval with a generative model to address complex information seeking tasks l

Beyond Static Sandboxing: Learned Capability Governance for Autonomous AI Agents

arXiv:2604.11839v1 Announce Type: cross Abstract: Autonomous AI agents built on open-source runtimes such as OpenClaw expose every available tool to every session by default, regardless of the task. A

Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs

arXiv:2604.12506v1 Announce Type: new Abstract: Recent Audio Large Language Models (AudioLLMs) exhibit a striking performance inversion: while excelling at complex reasoning tasks, they consistently u

safetyarxiv-cs-cl

Applications

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl

applicationsarxiv-cs-ai

Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks

arXiv:2604.12325v1 Announce Type: cross Abstract: We consider the problem of offline black-box optimization, where the goal is to discover optimal designs (e.g., molecules or materials) from past expe

BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities

arXiv:2603.27552v2 Announce Type: replace Abstract: Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed acr

agentsarxiv-cs-lg

Bridging the Micro--Macro Gap: Frequency-Aware Semantic Alignment for Image Manipulation Localization

arXiv:2604.12341v1 Announce Type: new Abstract: As generative image editing advances, image manipulation localization (IML) must handle both traditional manipulations with conspicuous forensic artifac

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