Search: “framework”

Probabilistic Attribution For Large Language Models

arXiv:2605.21726v1 Announce Type: new Abstract: The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the

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Psy-Chronicle:A Structured Pipeline for Synthesizing Long-Horizon Campus Psychological Counseling Dialogues

DGX agent

arXiv:2605.22140v1 Announce Type: new Abstract: In recent years, large language models have shown substantial potential in psychological support tasks. However, existing psychological counseling data

agentsarxiv-cs-cl

22 May 2026

Quantifying Full-Body Immersion

arXiv:2605.22521v1 Announce Type: new Abstract: Humanity is at the forefront of yet another digital revolution, where the lines between real and virtual worlds are dissolving, reshaping how we perceiv

researcharxiv-cs-ro

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks

arXiv:2605.22351v1 Announce Type: new Abstract: Low-bit quantization is widely used to compress super-resolution (SR) models and reduce storage and computation costs for deployment on resource-limited

safetyarxiv-cs-cv

RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation

model-releasesarxiv-cs-ai

arXiv:2605.20204v1 Announce Type: cross Abstract: LLM-based user simulation is the primary mechanism for end-to-end agent evaluation, yet simulated users are poor proxies for real humans: unconstraine

Reflective Prompt Tuning through Language Model Function-Calling

arXiv:2605.21781v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for

Residual Skill Optimization for Text-to-SQL Ensembles

arXiv:2605.21792v1 Announce Type: new Abstract: Text-to-SQL ensembles improve over single-candidate generation by drawing multiple SQL candidates and selecting one, but their effectiveness is bounded

Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning

arXiv:2602.23833v2 Announce Type: replace-cross Abstract: Automated identification of DICOM image series is essential for large-scale medical image analysis, quality control, protocol harmonization, a

Safe and Steerable Geometric Motion Policies for Robotic Dexterous Manipulation

arXiv:2605.21811v1 Announce Type: new Abstract: Robotic dexterous manipulation requires continuously reconciling objectives and constraints defined on heterogeneous geometric spaces: a robot controlle

safetyarxiv-cs-ro

ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving

arXiv:2605.21168v1 Announce Type: new Abstract: Safety-critical scenarios are central to evaluating autonomous driving systems, yet their rarity in naturalistic logs makes simulation-based stress test

safetyarxiv-cs-ai

Scout-Assisted Planning for Heterogeneous Robot Teams under Partially Known Environments

arXiv:2605.22693v1 Announce Type: new Abstract: Autonomous robot teams navigating partially known environments face costly backtracking when ground robots encounter blocked roads that are only reveale

agentsarxiv-cs-ro

Applications

SE3Kit: A Lightweight Python Library for Specialized Geometric Primitives in Robotics

arXiv:2605.22633v1 Announce Type: new Abstract: The Python robotics ecosystem faces a challenge: while many libraries exist for rigid body transformations, few are both lightweight and mathematically

applicationsarxiv-cs-ro

SegGuidedNet: Sub-Region-Aware Attention Supervision for Interpretable Brain Tumor Segmentation

arXiv:2605.22572v1 Announce Type: new Abstract: Accurate segmentation of brain tumour sub-regions from multi-parametric MRI is critical for treatment planning yet remains challenging due to morphologi

Tutorials

Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking

arXiv:2605.22538v1 Announce Type: new Abstract: Traditional visual object tracking (VOT) methods typically rely on task-specific supervised training, limiting their generalization to unseen objects an

tutorialsarxiv-cs-cv

Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

arXiv:2605.21852v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret invo

SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

arXiv:2512.10719v2 Announce Type: replace Abstract: End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual under

Applications

Spectral Tail Auxiliary Learning for AI-Generated Image Detection

arXiv:2605.22751v1 Announce Type: new Abstract: As generative image models evolve rapidly, the perceptual gap between generated and real images continues to narrow, making AI-generated image detection

applicationsarxiv-cs-cv

SPIRAL: Self-Evolving Action-Conditioned Video Generation via Reflective Planning Agents

arXiv:2603.08403v3 Announce Type: replace Abstract: Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

arXiv:2605.22158v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual token

stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation

arXiv:2605.21800v1 Announce Type: cross Abstract: World models are central to building agents that can reason, plan, and generalize beyond their training data. However, research on world models is cur

researcharxiv-cs-ro

Structural Anchor Pruning: Training-Free Multi-Vector Compression for Visual Document Retrieval

arXiv:2601.20107v2 Announce Type: replace-cross Abstract: Recent Vision-Language Models (e.g., ColPali) enable fine-grained Visual Document Retrieval (VDR) but incur prohibitive multi-vector index sto

Sub-exponential Growth Dynamics in Complex Systems: A Piecewise Power-Law Model for the Diffusion of New Words and Names

arXiv:2511.04106v5 Announce Type: replace-cross Abstract: The diffusion of ideas and language in society has conventionally been described by S-shaped models, such as the logistic curve. However, the

Tackle CSM in JPEG Steganalysis with Data Adaptation

arXiv:2605.21523v1 Announce Type: cross Abstract: Steganalysis models excel on benchmark datasets but struggle in the wild when analyzed images are produced by a processing pipeline unseen during trai

TacO: Benchmarking Tactile Sensors for Object Manipulation

arXiv:2605.21976v1 Announce Type: new Abstract: Vision-based learning from demonstrations has achieved remarkable success in enabling robots to perform manipulation tasks and high-level semantic reaso

safetyarxiv-cs-ro

Terminal Constraint Model Predictive Control for Image-Based Visual Servoing of UAVs with Kalman Filter-Based Moment Loss Compensation

arXiv:2605.22443v1 Announce Type: new Abstract: Image-Based Visual Servoing (IBVS) provides an efficient vision-guided control paradigm for unmanned aerial vehicles (UAVs) by directly regulating image

researcharxiv-cs-ro

The Double Dilemma in Multi-Task Radiology Report Generation: A Gradient Dynamics Analysis and Solution

arXiv:2605.22635v1 Announce Type: cross Abstract: While multi-task learning based automatic radiology report generation (RRG) is widely adopted to ensure clinical consistency, most focus on architectu

safetyarxiv-cs-cl

Time-varying rPPG signal separation via block-sparse signal model

arXiv:2605.22425v1 Announce Type: cross Abstract: Remote photoplethysmography (rPPG) enables non-contact measurement of cardiac pulse signals by analyzing subtle color changes in facial videos. Nevert

Token-Level LLM Collaboration via FusionRoute

arXiv:2601.05106v4 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strengths across diverse domains. However, achieving strong performance across these domains with a singl

Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration

arXiv:2605.20190v1 Announce Type: new Abstract: Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric ed

agentsarxiv-cs-ai

Towards Initialization-free Calibrated Bundle Adjustment

arXiv:2506.23808v2 Announce Type: replace Abstract: A recent series of works has shown that initialization-free BA can be achieved using pseudo Object Space Error (pOSE) as a surrogate objective. The

Towards Selection of Large Multimodal Models as Engines for Burned-in Protected Health Information Detection in Medical Images

arXiv:2511.02014v2 Announce Type: replace Abstract: The detection of Protected Health Information (PHI) in medical imaging is critical for safeguarding patient privacy and ensuring compliance with reg

Training-Free Fine-Grained Semantic Segmentations in Low Data Regimes: A FungiTastic Baseline

arXiv:2605.22492v1 Announce Type: new Abstract: Fine-grained semantic segmentation requires both precise localization and discrimination between visually similar classes. In FungiTastic, this problem

TWINGS: Thin Plate Splines Warp-aligned Initialization for Sparse-View Gaussian Splatting

arXiv:2605.22069v1 Announce Type: new Abstract: Novel view synthesis from sparse-view inputs poses a significant challenge in 3D computer vision, particularly for achieving high-quality scene reconstr

Unifying Masked Diffusion Models with Various Generation Orders and Beyond

arXiv:2602.02112v2 Announce Type: replace-cross Abstract: Masked diffusion models (MDMs) are a potential alternative to autoregressive models (ARMs) for language generation, but generation quality dep

safetyarxiv-cs-cl

UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation

arXiv:2605.21611v1 Announce Type: new Abstract: We introduce spatially grounded contextual image generation, a controllable image generation task that reframes the conditioning paradigm. Instead of su

Local Ai

VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals

arXiv:2605.20742v1 Announce Type: new Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly

local-aiarxiv-cs-ai

Tutorials

VChain: Chain-of-Visual-Thought for Reasoning in Video Generation

arXiv:2510.05094v2 Announce Type: replace Abstract: Recent video generation models can produce smooth and visually appealing clips, but they often struggle to synthesize complex dynamics with a cohere

tutorialsarxiv-cs-cv

VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents

arXiv:2602.00122v2 Announce Type: replace Abstract: In recent years, image editing models have made significant progress, enabling users to manipulate visual content in a flexible and interactive mann

VEELA: A Clinically-Constrained Benchmark for Liver Vessel Segmentation in Computed Tomography Angiography

arXiv:2605.22357v1 Announce Type: new Abstract: Accurate segmentation of hepatic and portal vessels in contrast-enhanced computed tomography angiography (CTA) remains challenging due to complex vascul

Video as Natural Augmentation: Towards Unified AI-Generated Image and Video Detection

arXiv:2605.21977v1 Announce Type: new Abstract: AI-generated content (AIGC) is rapidly improving, creating an urgent need for detectors that generalize across data sources, deployment pipelines, and v

Video-o3: Native Interleaved Clue Seeking for Long Video Multi-Hop Reasoning

arXiv:2601.23224v2 Announce Type: replace Abstract: Existing multimodal large language models for long-video understanding predominantly rely on uniform sampling and single-turn inference, limiting th

Virtual 3D H&E Staining from Phase-contrast Back-illumination Interference Tomography

arXiv:2605.22000v1 Announce Type: new Abstract: Three-dimensional (3D) histopathology of unprocessed tissues has the potential to transform disease management by enabling volumetric characterization o

VISTA: Validation-Guided Integration of Spatial and Temporal Foundation Models with Anatomical Decoding for Rare-Pathology VCE Event Detection -- after competition results

arXiv:2605.22096v1 Announce Type: new Abstract: Capsule endoscopy event detection is challenging because clinically relevant findings are sparse, visually heterogeneous, and evaluated at the event lev

Local Ai

VRXU-net: A Deep Learning Approach for Brain Ischemic Stroke Lesion Detection and Segmentation in T1W MRI

arXiv:2605.21633v1 Announce Type: cross Abstract: When the blood supply to the brain is obstructed by a clot, oxygen delivery to brain tissues becomes insufficient, leading to cellular necrosis. In he

local-aiarxiv-cs-cv

What Does the Caption Really Say? Counterfactual Phrase Intervention for Compositional Data Selection in Vision-Language Pretraining

arXiv:2605.22651v1 Announce Type: new Abstract: CLIP-style contrastive pretraining typically curates web-scale image-text pairs using sample-level filtering signals, often based on pair-level alignmen

safetyarxiv-cs-cv

What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom

arXiv:2602.01334v2 Announce Type: replace Abstract: Vision tool-use reinforcement learning (RL) can equip vision language models with visual operators such as crop-and-zoom and achieves strong perform

agentsarxiv-cs-cv

When Cases Get Rare: A Retrieval Benchmark for Off-Guideline Clinical Question Answering

arXiv:2605.21807v1 Announce Type: new Abstract: Across medical specialties, clinical practice is anchored in evidence-based guidelines that codify best studied diagnostic and treatment pathways. These

Why Semantic Entropy Fails: Geometry-Aware and Calibrated Uncertainty for Policy Optimization

arXiv:2605.21801v1 Announce Type: cross Abstract: Post-training has become central to improving reasoning and alignment in large language models, where critic-free models enable scalable learning from

safetyarxiv-cs-cl