Search: “research”

KD-CVG: A Knowledge-Driven Approach for Creative Video Generation

arXiv:2604.21362v1 Announce Type: new Abstract: Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a si

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot

DGX agent

arXiv:2604.21351v1 Announce Type: new Abstract: The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like

tutorialsarxiv-cs-ro

24 Apr 2026

Musical Score Understanding Benchmark: Evaluating Large Language Models' Comprehension of Complete Musical Scores

arXiv:2511.20697v4 Announce Type: replace-cross Abstract: Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of

Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance

arXiv:2604.21104v1 Announce Type: new Abstract: New geospatial foundation models introduce a new model architecture and pretraining dataset, often sampled using different notions of data diversity. Pe

Robustness Analysis of POMDP Policies to Observation Perturbations

arXiv:2604.21256v1 Announce Type: new Abstract: Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviat

SatSAM2: Motion-Constrained Video Object Tracking in Satellite Imagery using Promptable SAM2 and Kalman Priors

arXiv:2511.18264v3 Announce Type: replace Abstract: Existing satellite video tracking methods often struggle with generalization, requiring scenario-specific training to achieve satisfactory performan

Seeing Fast and Slow: Learning the Flow of Time in Videos

arXiv:2604.21931v1 Announce Type: cross Abstract: How can we tell whether a video has been sped up or slowed down? How can we generate videos at different speeds? Although videos have been central to

tutorialsarxiv-cs-ai

SparseGF: A Height-Aware Sparse Segmentation Framework with Context Compression for Robust Ground Filtering Across Urban to Natural Scenes

arXiv:2604.21356v1 Announce Type: new Abstract: High-quality digital terrain models derived from airborne laser scanning (ALS) data are essential for a wide range of geospatial analyses, and their gen

Survey on Evaluation of LLM-based Agents

arXiv:2503.16416v2 Announce Type: replace Abstract: LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environ

TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval

arXiv:2604.21806v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is an important image retrieval paradigm that enables users to retrieve a target image using a multimodal query that cons

Temporal Prototyping and Hierarchical Alignment for Unsupervised Video-based Visible-Infrared Person Re-Identification

arXiv:2604.21324v1 Announce Type: new Abstract: Visible-infrared person re-identification (VI-ReID) enables cross-modality identity matching for all-day surveillance, yet existing methods predominantl

The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality

arXiv:2604.20569v1 Announce Type: cross Abstract: Automatic systems are increasingly used to assess the originality of responses in creative tasks. They offer a potential solution to key limitations o

The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

arXiv:2604.21312v1 Announce Type: cross Abstract: This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The

Agents

The Last Harness You'll Ever Build

arXiv:2604.21003v1 Announce Type: new Abstract: AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require dozens of clicks and fo

agentsarxiv-cs-ai

Thinking Like a Botanist: Challenging Multimodal Language Models with Intent-Driven Chain-of-Inquiry

arXiv:2604.20983v1 Announce Type: cross Abstract: Vision evaluations are typically done through multi-step processes. In most contemporary fields, experts analyze images using structured, evidence-bas

'This Wasn't Made for Me': Recentering User Experience and Emotional Impact in the Evaluation of ASR Bias

arXiv:2604.21148v1 Announce Type: new Abstract: Studies on bias in Automatic Speech Recognition (ASR) tend to focus on reporting error rates for speakers of underrepresented dialects, yet less researc

safetyarxiv-cs-cl

Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception

arXiv:2604.20895v1 Announce Type: cross Abstract: Safety and security are essential for the admission and acceptance of automated and autonomous vehicles. Deep neural networks (DNNs) are widely used f

safetyarxiv-cs-lg

Local Ai

Ufil: A Unified Framework for Infrastructure-based Localization

arXiv:2604.21471v1 Announce Type: new Abstract: Infrastructure-based localization enhances road safety and traffic management by providing state estimates of road users. Development is hindered by fra

local-aiarxiv-cs-ro

VG-CoT: Towards Trustworthy Visual Reasoning via Grounded Chain-of-Thought

arXiv:2604.21396v1 Announce Type: cross Abstract: The advancement of Large Vision-Language Models (LVLMs) requires precise local region-based reasoning that faithfully grounds the model's logic in act

When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors

model-releasesarxiv-cs-cl

arXiv:2604.21255v1 Announce Type: new Abstract: Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents sh

When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs

arXiv:2604.21911v1 Announce Type: cross Abstract: Despite impressive progress in capabilities of large vision-language models (LVLMs), these systems remain vulnerable to hallucinations, i.e., outputs

AI models of unstable flow exhibit hallucination

arXiv:2604.20372v1 Announce Type: cross Abstract: We report the first systematic evidence of hallucination in AI models of fluid dynamics, demonstrated in the canonical problem of hydrodynamically uns

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization

arXiv:2604.20748v1 Announce Type: new Abstract: Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although exist

applicationsarxiv-cs-cv

ATIR: Towards Audio-Text Interleaved Contextual Retrieval

arXiv:2604.20267v1 Announce Type: cross Abstract: Audio carries richer information than text, including emotion, speaker traits, and environmental context, while also enabling lower-latency processing

AVISE: Framework for Evaluating the Security of AI Systems

arXiv:2604.20833v1 Announce Type: cross Abstract: As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-p

Benchmarking ResNet for Short-Term Hypoglycemia Classification with DiaData

arXiv:2511.02849v2 Announce Type: replace-cross Abstract: Individualized therapy is driven forward by medical data analysis, which provides insight into the patient's context. In particular, for Type

Agents

Can LLMs Infer Conversational Agent Users' Personality Traits from Chat History?

arXiv:2604.19785v1 Announce Type: cross Abstract: Sensitive information, such as knowledge about an individual's personality, can be can be misused to influence behavior (e.g., via personalized messag

agentsarxiv-cs-ai

Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples

arXiv:2604.20824v1 Announce Type: new Abstract: The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch

applicationsarxiv-cs-lg

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training

arXiv:2604.20012v1 Announce Type: cross Abstract: Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from

Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models

model-releasesarxiv-cs-lg

arXiv:2508.17761v3 Announce Type: replace Abstract: In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonl

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation

arXiv:2506.21095v4 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative training while preserving privacy, yet it introduces a critical challenge: the 'illusion of fair

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems

arXiv:2508.15411v3 Announce Type: replace-cross Abstract: Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. Ho

tutorialsarxiv-cs-cl

Graph-Theoretic Models for the Prediction of Molecular Measurements

model-releasesarxiv-cs-lg

arXiv:2604.19840v1 Announce Type: new Abstract: Graph-theoretic approaches offer simplicity, interpretability, and low computational cost for molecular property prediction. Among these, the model prop

Improving Large-Scale Recommender Systems with Auxiliary Learning

arXiv:2510.02215v3 Announce Type: replace Abstract: Training large-scale recommendation models under a single global objective implicitly assumes homogeneity across user populations. However, real-wor

applicationsarxiv-cs-lg

JoyAI-RA 0.1: A Foundation Model for Robotic Autonomy

arXiv:2604.20100v1 Announce Type: new Abstract: Robotic autonomy in open-world environments is fundamentally limited by insufficient data diversity and poor cross-embodiment generalization. Existing r

applicationsarxiv-cs-ro

KOCO-BENCH: Can Large Language Models Leverage Domain Knowledge in Software Development?

arXiv:2601.13240v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel at general programming but struggle with domain-specific software development, necessitating domain special

LayerTracer: A Joint Task-Particle and Vulnerable-Layer Analysis framework for Arbitrary Large Language Model Architectures

arXiv:2604.20556v1 Announce Type: cross Abstract: Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba. How

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management

arXiv:2601.11505v2 Announce Type: replace-cross Abstract: Progress in Type 1 Diabetes (T1D) algorithm development is limited by the fragmentation and lack of standardization across existing T1D manage

OnSiteVRU: A High-Resolution Trajectory Dataset for High-Density Vulnerable Road Users

arXiv:2503.23365v2 Announce Type: replace Abstract: With the acceleration of urbanization and the growth of transportation demands, the safety of vulnerable road users (VRUs, such as pedestrians and c

PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models

arXiv:2604.19773v1 Announce Type: cross Abstract: The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large langu

Sampling-Aware Quantization for Diffusion Models

arXiv:2505.02242v2 Announce Type: replace Abstract: Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computatio

Agents

Shift-Up: A Framework for Software Engineering Guardrails in AI-native Software Development -- Initial Findings

arXiv:2604.20436v1 Announce Type: cross Abstract: Generative AI (GenAI) is reshaping software engineering by shifting development from manual coding toward agent-driven implementation. While vibe codi

agentsarxiv-cs-ai

Throat and acoustic paired speech dataset for deep learning-based speech enhancement

arXiv:2502.11478v3 Announce Type: replace-cross Abstract: In high-noise environments such as factories, subways, and busy streets, capturing clear speech is challenging. Throat microphones can offer a

safetyarxiv-cs-lg

Towards Event-Aware Forecasting in DeFi: Insights from On-chain Automated Market Maker Protocols

model-releasesarxiv-cs-lg

arXiv:2604.20374v1 Announce Type: new Abstract: Automated Market Makers (AMMs), as a core infrastructure of decentralized finance (DeFi), uniquely drive on-chain asset pricing through a deterministic

Towards Secure Logging: Characterizing and Benchmarking Logging Code Security Issues with LLMs

arXiv:2604.20211v1 Announce Type: cross Abstract: Logging code plays an important role in software systems by recording key events and behaviors, which are essential for debugging and monitoring. Howe

Transformers Can Learn Connectivity in Some Graphs but Not Others

arXiv:2509.22343v2 Announce Type: replace-cross Abstract: Reasoning capability is essential to ensure the factual correctness of the responses of transformer-based Large Language Models (LLMs), and ro

tutorialsarxiv-cs-ai

What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization

arXiv:2601.17609v2 Announce Type: replace Abstract: In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that str

applicationsarxiv-cs-cl