Search: “framework”

Divide and Contrast: Learning Robust Temporal Features without Augmentation

arXiv:2605.21241v1 Announce Type: new Abstract: Self-supervised learning for time-series representation aims to reduce reliance on labeled data while maintaining strong downstream performance, yet man

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Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models

DGX agent

arXiv:2605.20591v1 Announce Type: new Abstract: Medical large language models (LLMs), including custom medical GPTs (MedGPTs) and open-source models, are increasingly deployed on web platforms to prov

safetyarxiv-cs-cl

21 May 2026

Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interaction

arXiv:2605.20743v1 Announce Type: cross Abstract: Vision-language models solve geometry problems with rising accuracy, yet their intermediate states remain latent and unverifiable: a relation expresse

agentsarxiv-cs-cl

DrawMotion: Generating 3D Human Motions by Freehand Drawing

arXiv:2605.20955v1 Announce Type: new Abstract: Text-to-motion generation, which translates textual descriptions into human motions, faces the challenge that users often struggle to precisely convey t

DriveMA: Rethinking Language Interfaces in Driving VLAs with One-Step Meta-Actions

arXiv:2605.21273v1 Announce Type: new Abstract: Driving Vision-Language-Action Models (Driving VLAs) commonly introduce natural-language reasoning as an intermediate interface for end-to-end planning,

Dynamic Shapley Computation

arXiv:2605.20620v1 Announce Type: new Abstract: Shapley-based data valuation provides a principled way to quantify the contribution of training data, but its high computational cost makes it impractic

researcharxiv-cs-lg

Dynamic Video Generation: Shaping Video Generation Across Time and Space

arXiv:2605.21042v1 Announce Type: new Abstract: Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due t

DySink: Dynamic Frame Sinks for Autoregressive Long Video Generation

arXiv:2605.21028v1 Announce Type: new Abstract: Autoregressive long video generation often adopts bounded-memory streaming for efficiency, typically combining local windows for short-term continuity w

Efficient Table QA via TableGrid Navigation and Progressive Inference Prompting

arXiv:2605.20254v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown promising results on NLP tasks, however, their performance on tabular data still needs research attention, bec

End2Reg: Learning Task-Specific Segmentation for Markerless Registration in Spine Surgery

arXiv:2512.13402v2 Announce Type: replace Abstract: Intraoperative navigation in spine surgery demands millimeter-level accuracy. Currently, this is achieved through radiation-intensive intraoperative

Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computing

arXiv:2605.21213v1 Announce Type: cross Abstract: In this work, we present quantum reinforcement learning (RL) as a solution strategy for process synthesis problems. Building on our prior work, we dev

Enhancing Graph-Based SLAM in GNSS-Denied environments by leveraging leg odometry

arXiv:2605.20484v1 Announce Type: new Abstract: Autonomous navigation in GNSS-denied environments remains a core challenge for legged robots, where exteroceptive sensors such as LiDAR are prone to ele

agentsarxiv-cs-ro

Enhancing Speech Large Language Models through Reinforced Behavior Alignment

arXiv:2509.03526v2 Announce Type: replace Abstract: The recent advancements of Large Language Models (LLMs) have spurred considerable research interest in extending their linguistic capabilities beyon

safetyarxiv-cs-cl

EPC-3D-Diff: Equivariant Physics Consistent Conditional 3D Latent Diffusion for CBCT to CT Synthesis

arXiv:2605.20470v1 Announce Type: new Abstract: Cone-beam CT (CBCT) is routinely acquired during radiotherapy for patient setup, but its quantitative reliability is degraded by scatter, noise, and rec

EpiCache: Episodic KV Cache Management for Long-Term Conversation on Resource-Constrained Environments

arXiv:2509.17396v4 Announce Type: replace Abstract: Modern large language models (LLMs) extend context lengths to millions of tokens, enabling coherent, personalized responses grounded in long convers

researcharxiv-cs-cl

Everywhere Valid Bounds on False Discovery Proportions in Conformal Inference

arXiv:2605.20726v1 Announce Type: cross Abstract: Modern applications of conformal inference to multiple testing problems, such as outlier detection and candidate selection, often involve selecting te

researcharxiv-cs-lg

Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning

arXiv:2605.20551v1 Announce Type: new Abstract: Visual Place Recognition (VPR) aims to match a query image to reference images of the same place in a large-scale database. Recent state-of-the-art meth

Fault-Tolerant, Rigidity-Preserving Control of Inflatable Truss Robots

arXiv:2605.20561v1 Announce Type: new Abstract: Isoperimetric robotic trusses can adapt to different tasks and environments because they have a high strength-to-weight ratio, can change their own shap

researcharxiv-cs-ro

FBOS-RL: Feedback-Driven Bi-Objective Synergistic Reinforcement Learning

arXiv:2605.20256v1 Announce Type: new Abstract: Reinforcement learning has become a cornerstone for aligning and unlocking the reasoning capabilities of large-scale models. At its core, the training l

FedCoE: Bridging Generalization and Personalization via Federated Coordinated Dual-level MoEs

arXiv:2605.21264v1 Announce Type: new Abstract: Federated Learning (FL) has emerged as a promising paradigm for privacy-preserving distributed learning. However, existing FL methods face a fundamental

FedCritic: Serverless Federated Critic Learning-based Resource Allocation for Multi-Cell OFDMA in 6G

arXiv:2605.21418v1 Announce Type: cross Abstract: In sixth-generation (6G) ultra-dense networks, aggressive frequency reuse amplifies inter-cell interference (ICI), making multi-cell orthogonal freque

Federated LoRA Fine-Tuning for LLMs via Collaborative Alignment

arXiv:2605.21217v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has emerged as a powerful tool for parameter-efficient fine-tuning of large language models (LLMs). This paper studies LoRA

FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents

arXiv:2603.01712v2 Announce Type: replace-cross Abstract: Fine-tuning large language models for vertical domains remains labor-intensive, requiring practitioners to curate data, configure training, an

GAMR: Geometric-Aware Manifold Regularization with Virtual Outlier Synthesis for Learning with Noisy Labels

arXiv:2605.20727v1 Announce Type: new Abstract: Deep neural networks (DNNs) experience significant performance degradation when processing noisy labels, primarily due to overfitting on mislabeled data

safetyarxiv-cs-cv

Gaussian Sheaf Neural Networks

arXiv:2605.21435v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have become the de facto standard for learning on relational data. While traditional GNNs' message passing is well suited f

Generation of Heterogeneous PET Images from Uniform Organ Activity Maps Using a Pretrained Domain-Adapted Diffusion Model

arXiv:2605.20267v1 Announce Type: new Abstract: Synthetic PET images are valuable for quantitative imaging workflow development, scalable virtual imaging trials, and deep learning model training, but

Graph Autoencoder for Process Monitoring

arXiv:2602.03004v2 Announce Type: replace Abstract: To improve the reliability and interpretability of industrial process monitoring, this article proposes a Causal Graph Spatial-Temporal Autoencoder

GraphDiffMed: Knowledge-Constrained Differential Attention with Pharmacological Graph Priors for Medication Recommendation

arXiv:2605.20188v1 Announce Type: new Abstract: Recommending safe and effective medication combinations from electronic health records (EHRs) is a core clinical AI problem, yet it remains difficult be

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

arXiv:2605.20600v1 Announce Type: new Abstract: Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching

tutorialsarxiv-cs-cv

HITL-D: Human In The Loop Diffusion Assisted Shared Control

arXiv:2605.21460v1 Announce Type: new Abstract: Autonomous manipulation systems have achieved remarkable capabilities, yet the integration of human expertise with diffusion-based policies in shared co

agentsarxiv-cs-ro

How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective

arXiv:2502.17773v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate survey responses, but synthetic data can be misaligned with the human populatio

researcharxiv-cs-lg

How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study

arXiv:2604.06750v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) are increasingly proposed for autonomous driving tasks, yet their performance on sequential driving scenes remains poo

agentsarxiv-cs-cv

'I didn't Make the Micro Decisions': Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration

arXiv:2605.21363v1 Announce Type: new Abstract: As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration b

applicationsarxiv-cs-cl

Local Ai

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools

arXiv:2605.20682v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown remarkable capability in bridging visual perception and textual reasoning, enabling zero-shot unders

local-aiarxiv-cs-cv

Inference Time Policy Optimization for Offline RL with Differentiable World Models

arXiv:2603.22430v2 Announce Type: replace Abstract: Offline Reinforcement Learning (RL) learns optimal policies from fixed datasets, training a policy once and deploying it at inference time without f

Hardware

Instant GPU Efficiency Visibility at Fleet Scale

arXiv:2605.20799v1 Announce Type: cross Abstract: We present Overall FLOP Utilization (OFU), a hardware-level, precision-agnostic GPU efficiency metric for AI workloads on HPC systems, derived from tw

hardwarearxiv-cs-lg

Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning

arXiv:2605.21475v1 Announce Type: new Abstract: Relational prediction tasks are fundamental in many real-world applications, where data are naturally stored in relational databases (RDBs). Relational

It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs

arXiv:2605.20258v1 Announce Type: new Abstract: Contextual Integrity (CI) defines privacy not merely as keeping information hidden, but as governing information flows according to the norms of a given

iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance

arXiv:2605.21431v1 Announce Type: new Abstract: Video Virtual Try-On (VVT) aims to seamlessly replace a garment on a person in a video with a new one. While existing methods have made significant stri

tutorialsarxiv-cs-cv

JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Media

model-releasesarxiv-cs-cl

arXiv:2605.20960v1 Announce Type: new Abstract: This paper introduces JobArabi, a large-scale corpus of Arabic job announcements collected from social media between January 2024 and October 2025. The

JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA

arXiv:2605.20284v1 Announce Type: new Abstract: Industrial anomaly detection has been significantly advanced by Large Multimodal Models (LMMs), enabling diverse human instructions beyond detection, pa

LASH: Adaptive Semantic Hybridization for Black-Box Jailbreaking of Large Language Models

arXiv:2605.21362v1 Announce Type: new Abstract: Jailbreak attacks expose a persistent gap between the intended safety behavior of aligned large language models and their behavior under adversarial pro

safetyarxiv-cs-cl

Latent Geometry as a Structural Monitor: Eigenspace Alignment for Anomaly Detection in Anonymity Networks

arXiv:2605.20391v1 Announce Type: cross Abstract: Traditional anomaly detection marks events when measured signals cross predefined thresholds. This captures the moment of transition but not the struc

Latent Process Generator Matching

arXiv:2605.20547v1 Announce Type: new Abstract: Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to

tutorialsarxiv-cs-lg

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

model-releasesarxiv-cs-cl

arXiv:2602.06025v2 Announce Type: replace Abstract: Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offl

Learning to Defer in Non-Stationary Time Series via Switching State-Space Models

arXiv:2601.22538v2 Announce Type: replace Abstract: Learning-to-defer (L2D) routes each decision to a system's own predictor or to an external expert. Streaming time-series settings break the offline-

tutorialsarxiv-cs-lg

Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment

arXiv:2605.20780v1 Announce Type: cross Abstract: Physics-informed diffusion models typically enforce PDE constraints only on final outputs, leaving intermediate representations unconstrained and pron

safetyarxiv-cs-cv

LER-YOLO: Reliability-Aware Expert Routing for Misaligned RGB-Infrared UAV Detection

arXiv:2605.20667v1 Announce Type: new Abstract: Detecting small unmanned aerial vehicles from RGB-infrared remote-sensing pairs remains challenging due to tiny target scale, cluttered backgrounds, and