Search: “synthesis”

RadarSim: Simulating Single-Chip Radar via Multimodal Neural Fields

arXiv:2605.26328v1 Announce Type: new Abstract: Radars are an ideal complement to cameras: both are inexpensive, solid-state sensors, with cameras offering fine angular resolution, while radars provid

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Research

Slide Deck Q&A Quality Assurance App: A Multi-Stage Pipeline for Pedagogical Question Generation

DGX agent

arXiv:2605.26428v1 Announce Type: new Abstract: Generating high-quality, pedagogically useful questions from lecture slide decks is difficult because important instructional content is distributed acr

researcharxiv-cs-cl

27 May 2026

SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2603.28730v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown impressive capabilities across diverse tasks, motivating efforts to leverage these models to supervis

Underwater360: Reconstructing Underwater Scenes from Panoramic Images with Omnidirectional Gaussian Splatting

arXiv:2605.26447v1 Announce Type: new Abstract: Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-med

VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models

arXiv:2510.17759v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) extend large language models with visual reasoning, but their multimodal design also introduces new, underexplor

safetyarxiv-cs-cl

Applications

VesselSim: learning 3D blood vessel segmentation without expert annotations

arXiv:2605.26277v1 Announce Type: cross Abstract: Blood vessel segmentation is a core task in medical image analysis for the care of vascular diseases and surgical planning, yet the challenges of prov

applicationsarxiv-cs-ai

AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond

arXiv:2605.26113v1 Announce Type: new Abstract: Generating high-fidelity and controllable synthetic data is critical for advancing end-to-end autonomous driving, particularly for addressing the long t

safetyarxiv-cs-ro

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

BODHI: Precise OS Kernel Specification Inference

arXiv:2605.23931v1 Announce Type: new Abstract: The formal verification of operating system kernels requires precise specifications that capture the intended behavior of system calls. Writing these sp

Cross-Domain Generalization Limits of Vision Foundation Models in Facial Deepfake Detection

arXiv:2605.24965v1 Announce Type: cross Abstract: The rapid evolution of generative models has enabled the creation of hyper-realistic facial deepfakes, exposing a critical vulnerability in modern dig

CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents

arXiv:2605.25624v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its exte

D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation

arXiv:2605.25022v1 Announce Type: cross Abstract: Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing stud

Tutorials

Designing Singing Syllabi with Virtual Avatars: AI-Assisted Syllabus Reauthoring

arXiv:2508.11872v3 Announce Type: replace-cross Abstract: Traditional syllabi often function as static reference documents rather than engaging introductions to a course. In practical teaching, we obs

tutorialsarxiv-cs-ai

Energy Shields for Fairness

arXiv:2605.24926v1 Announce Type: new Abstract: Runtime fairness is not a one-time constraint but a dynamic property evaluated over a sequence of decisions. To ensure fairness at runtime, it is necess

Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning

arXiv:2605.24844v1 Announce Type: new Abstract: While general-purpose Large Language Models (LLMs) applied to Geology often hallucinate when reasoning about subsurface structures and deep-time evoluti

IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization

model-releasesarxiv-cs-lg

arXiv:2605.24659v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed for complex tasks requiring planning, tool use, and interaction with external services. Their reliance on unt

KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI

arXiv:2510.02327v2 Announce Type: replace-cross Abstract: Real-time speech-to-speech (S2S) models excel at generating natural, low-latency conversational responses but often lack deep knowledge and se

MDIA: A Multi-Agent Diagnostic Intelligence Pipeline on HealthBench Professional

arXiv:2605.24699v1 Announce Type: new Abstract: Most reported gains on agentic-LLM clinical benchmarks are often attributed to prompt engineering, yet our results suggest that larger improvements can

MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

model-releasesarxiv-cs-ro

arXiv:2605.26006v1 Announce Type: cross Abstract: Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typic

Agents

Multi-Persona Debate System for Automated Scientific Hypothesis Generation

arXiv:2605.23917v1 Announce Type: new Abstract: Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. Th

agentsarxiv-cs-cl

Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation

arXiv:2605.25220v1 Announce Type: cross Abstract: High-fidelity 3D Gaussian head avatar generation is critical for applications such as AR/VR, telepresence, and digital humans. Existing methods depend

safetyarxiv-cs-ro

Multimodal Alignment and Preference Optimization for Zero-Shot Conditional RNA Generation

arXiv:2605.23961v1 Announce Type: cross Abstract: The design of RNA molecules that interact with specific proteins is a critical challenge in experimental and computational biology. Despite recent pro

OrpQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization

arXiv:2605.26092v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) and Vision Transformers (ViTs) on edge devices is significantly constrained by memory limitations and t

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering

arXiv:2605.24792v1 Announce Type: cross Abstract: The major limitations of gastrointestinal (GI) endoscopy AI systems arise from a shortage of annotated data, strict privacy policies, and significant

Agents

PRIMA: Operational Patterns for Resilient Multi-Agent Research with Verifiable Identity and Convergent Feedback

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

agentsarxiv-cs-ai

Applications

RCTs & Human Uplift Studies: Methodological Challenges and Practical Solutions for Frontier AI Evaluation

arXiv:2603.11001v2 Announce Type: replace-cross Abstract: Human uplift studies, or studies that measure the effects of AI access on human performance via randomized controlled trials (RCT) or similar

applicationsarxiv-cs-ai

Re-defining Humor Data Objects for AI Humor Research

arXiv:2605.25171v1 Announce Type: new Abstract: In most existing AI humor research, humor was treated as either 'present' or 'not present.' We explore the concept of humor as a social interaction with

researcharxiv-cs-cl

Hardware

SA-Kura: An Energy-Efficient Systolic Array Accelerator for Locally-Coupled Kuramoto Drift in Diffusion Sampling

arXiv:2605.24016v1 Announce Type: cross Abstract: Diffusion inference remains costly for edge deployment, yet existing accelerators focus almost exclusively on score networks because standard drift is

hardwarearxiv-cs-ai

The Time is Here for Just-in-Time Systems: Challenges and Opportunities

arXiv:2605.24096v1 Announce Type: cross Abstract: Core systems like key-value stores have historically taken years to build, and are designed to be general so as to amortize cost across deployments, p

Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models

arXiv:2605.22896v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for robotic manipulation by leveraging pre-trained vision-language representa

Diffusion and Flow Matching Models for Tabular Data: A Survey

arXiv:2502.17119v2 Announce Type: replace-cross Abstract: Deep generative models have made rapid progress in image, text, audio, and video generation, and are increasingly being applied to structured

Efficient One-Step Diffusion Restoration Model with Compact Token Compression and Linear Attention

arXiv:2605.23451v1 Announce Type: new Abstract: Real-world image super-resolution aims to recover high-quality images from complex and unknown real-world degradations. However, existing generative Rea

Applications

Knowledge Distillation for Low-Resource Open-source Text-to-SQL Model

arXiv:2605.22843v1 Announce Type: new Abstract: Text-to-SQL converts natural language questions into executable SQL queries, enabling non-technical users to access relational databases for analytics a

applicationsarxiv-cs-cl

LangFlash: Feed-forward 3D Language Gaussian Splatting from Sparse Unposed Images

arXiv:2605.23287v1 Announce Type: new Abstract: We present LangFlash, a feed-forward framework for 3D Language Gaussian Splatting that reconstructs 3D scenes parameterized by Gaussian primitives enric

R^3L: Reflect-then-Retry Reinforcement Learning with Language-Guided Exploration, Pivotal Credit, and Positive Amplification

arXiv:2601.03715v2 Announce Type: replace-cross Abstract: Reinforcement learning drives recent advances in LLM reasoning and agentic capabilities, yet current approaches struggle with both exploration

Tutorials

RiGS: Rigid-aware 4D Gaussian Splatting from a Single Monocular Video

arXiv:2605.23672v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from monocular videos is a fundamental yet highly challenging task, as real-world motions often involve both long-term

tutorialsarxiv-cs-cv

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen

VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset

arXiv:2605.23518v1 Announce Type: new Abstract: Directly editing ultra-high-resolution (UHR) images is valuable but underexplored, primarily due to the lack of high-quality data and the challenge in m

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models

arXiv:2603.02938v2 Announce Type: replace Abstract: Graph-based tasks in the zero-shot setting remain a significant challenge due to data scarcity and the inability of traditional Graph Neural Network

safetyarxiv-cs-lg

23 May 2026

Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators

arXiv:2605.22717v1 Announce Type: cross Abstract: Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline mode

safetyarxiv-cs-lg

23 May 2026

TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting

arXiv:2605.22365v1 Announce Type: cross Abstract: Time Series Forecasting (TSF) plays a critical role across many domains, yet it is vulnerable to backdoor attacks. However, backdoor defenses tailored

researcharxiv-cs-lg

23 May 2026

Agents

ACC: Compiling Agent Trajectories for Long-Context Training

arXiv:2605.21850v1 Announce Type: new Abstract: Recent development of agents has renewed demand for long-context reasoning capacity of LLMs. However, training LLMs for this capacity requires costly lo

agentsarxiv-cs-cl

AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculture

arXiv:2605.22366v1 Announce Type: new Abstract: Agricultural decision-making increasingly requires multimodal systems that can transform visual observations into reliable, executable actions. However,

Cell Phantom Video Generation in Elliptical Fourier Descriptor Domain

arXiv:2605.22563v1 Announce Type: new Abstract: Training Deep Neural Networks for tracking individual cells in biomedical videos requires a large amount of annotated data. The annotation of videos for

Hardware

EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation

arXiv:2605.22051v1 Announce Type: new Abstract: Generating high-fidelity visual effects (VFX) typically demands massive datasets and prohibitive computational power due to the intricate coupling of sp

hardwarearxiv-cs-cv

Evaluating Commercial AI Chatbots as News Intermediaries

model-releasesarxiv-cs-cl

arXiv:2605.22785v1 Announce Type: new Abstract: AI chatbots are rapidly shaping how people encounter the news, yet no prior study has systematically measured how accurately these systems, with their p

EventGait: Towards Robust Gait Recognition with Event Streams

arXiv:2605.22139v1 Announce Type: new Abstract: Gait recognition enables non-intrusive, privacy-preserving identification but suffers in uncontrolled environments due to illumination and motion sensit

Guided Trajectory Optimization with Sparse Scaling for Test-Time Diffusion

arXiv:2605.21907v1 Announce Type: new Abstract: The efficient Test-Time Scaling (TTS) paradigm offers a promising perspective for enhancing the generation performance of diffusion models. However, cur