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arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper

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Learning from Imperfect Text Guidance: Robust Long-Tail Visual Recognition with High-Noise Label

DGX agent

arXiv:2604.23125v1 Announce Type: new Abstract: Real-world data often exhibit long-tailed distributions with numerous noisy labels, substantially degrading the performance of deep models. While prior

safetyarxiv-cs-cv

28 Apr 2026

Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain

arXiv:2509.10546v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most r

Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation

arXiv:2604.23604v1 Announce Type: new Abstract: Understanding the surrounding environment is fundamental in autonomous driving and robotic perception. Distinguishing between known classes and previous

agentsarxiv-cs-cv

LLM4SCREENLIT: Recommendations on Assessing the Performance of Large Language Models for Screening Literature in Systematic Reviews

arXiv:2511.12635v2 Announce Type: replace-cross Abstract: Context: Large language models (LLMs) are increasingly used to screen literature for systematic reviews (SRs), but the standard confusion-matr

OLaPh: Optimal Language Phonemizer

arXiv:2509.20086v2 Announce Type: replace Abstract: Phonemization is a critical component in text-to-speech synthesis. Traditional approaches rely on deterministic transformations and lexica, while ne

On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning

model-releasesarxiv-cs-lg

arXiv:2507.06542v4 Announce Type: replace Abstract: Decentralized learning provides a scalable alternative to parameter-server-based training, yet its performance is often hindered by limited peer-to-

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving

arXiv:2604.23712v1 Announce Type: cross Abstract: Recent advances in formal theorem proving have focused on Olympiad-level mathematics, leaving undergraduate domains largely unexplored. Optimization,

Orthogonal Representation Learning for Estimating Causal Quantities

arXiv:2502.04274v4 Announce Type: replace Abstract: End-to-end representation learning has become a powerful tool for estimating causal quantities from high-dimensional observational data, but its eff

safetyarxiv-cs-lg

Overcoming Copyright Barriers in Corpus Distribution Through Non-Reversible Hashing

arXiv:2604.23412v1 Announce Type: new Abstract: While annotated corpora are crucial in the field of natural language processing (NLP), those containing copyrighted material are difficult to exchange a

safetyarxiv-cs-cl

PivotMerge: Bridging Heterogeneous Multimodal Pre-training via Post-Alignment Model Merging

arXiv:2604.22823v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) rely on multimodal pre-training over diverse data sources, where different datasets often induce complementar

Probing Visual Planning in Image Editing Models

arXiv:2604.22868v1 Announce Type: cross Abstract: Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in m

tutorialsarxiv-cs-ai

QEVA: A Reference-Free Evaluation Metric for Narrative Video Summarization with Multimodal Question Answering

arXiv:2604.24052v1 Announce Type: cross Abstract: Video-to-text summarization remains underexplored in terms of comprehensive evaluation methods. Traditional n-gram overlap-based metrics and recent la

Quantum Knowledge Graph: Modeling Context-Dependent Triplet Validity

arXiv:2604.23972v1 Announce Type: cross Abstract: Knowledge graphs (KGs) are increasingly used to support large lan guage model (LLM) reasoning, but standard triplet-based KGs treat each relation as g

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization

arXiv:2408.00923v2 Announce Type: replace-cross Abstract: This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by fram

Local Ai

Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems

arXiv:2602.04120v2 Announce Type: replace-cross Abstract: Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most

local-aiarxiv-cs-ai

Scheming Ability in LLM-to-LLM Strategic Interactions

arXiv:2510.12826v2 Announce Type: replace-cross Abstract: As large language model (LLM) agents are deployed autonomously in diverse contexts, evaluating their capacity for strategic deception becomes

ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services

arXiv:2604.24023v1 Announce Type: new Abstract: Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their p

SFT-then-RL Outperforms Mixed-Policy Methods for LLM Reasoning

arXiv:2604.23747v1 Announce Type: cross Abstract: Recent mixed-policy optimization methods for LLM reasoning that interleave or blend supervised and reinforcement learning signals report improvements

ShredBench: Evaluating the Semantic Reasoning Capabilities of Multimodal LLMs in Document Reconstruction

arXiv:2604.23813v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance in Visually Rich Document Understanding (VRDU) tasks, but their capabili

SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning

arXiv:2506.05425v2 Announce Type: replace-cross Abstract: Understanding social interaction, which encompasses perceiving numerous and subtle multimodal cues, inferring unobservable mental states and r

Skill Retrieval Augmentation for Agentic AI

arXiv:2604.24594v1 Announce Type: cross Abstract: As large language models (LLMs) evolve into agentic problem solvers, they increasingly rely on external, reusable skills to handle tasks beyond their

SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing

arXiv:2604.23392v1 Announce Type: new Abstract: Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widel

SolarFCD: A Large-Scale Dataset and Benchmark for Solar Fault Classification in Photovoltaic Systems

arXiv:2604.23662v1 Announce Type: new Abstract: The increasing global deployment of solar photovoltaic (PV) systems needs robust, scalable, and automated inspection technologies capable of detecting a

Structure Guided Retrieval-Augmented Generation for Factual Queries

arXiv:2604.22843v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has been proposed to mitigate hallucinations in large language models (LLMs), where generated outputs may be fact

tutorialsarxiv-cs-ai

Survey in Characterizing Semantic Change

arXiv:2402.19088v5 Announce Type: replace-cross Abstract: Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words

tutorialsarxiv-cs-ai

The Consensus Trap: Dissecting Subjectivity and the 'Ground Truth' Illusion in Data Annotation

arXiv:2602.11318v3 Announce Type: replace Abstract: In machine learning, 'ground truth' refers to the assumed correct labels used to train and evaluate models. However, the foundational 'ground truth'

safetyarxiv-cs-ai

The High Cost of Incivility: Quantifying Interaction Inefficiency via Multi-Agent Monte Carlo Simulations

arXiv:2512.08345v2 Announce Type: replace Abstract: Workplace toxicity is widely recognized as detrimental to organizational culture, yet quantifying its direct impact on operational efficiency remain

agentsarxiv-cs-ai

Verifying Quantized GNNs With Readout Is Decidable But Highly Intractable

arXiv:2510.08045v2 Announce Type: replace-cross Abstract: We introduce a logical language for reasoning about quantized aggregate-combine graph neural networks with global readout (ACR-GNNs). We provi

safetyarxiv-cs-ai

WebSerial Vision Training for Microcontrollers: A Browser-Based Companion to On-Device CNN Training

arXiv:2604.22834v1 Announce Type: new Abstract: This paper presents webmcu-vision-web, a single-file, zero-install browser application for end-to-end TinyML vision model training and deployment on the

X-NegoBox: An Explainable Privacy-Budget Negotiation Framework for Secure Peer-to-Peer Energy Data Exchange

arXiv:2604.24326v1 Announce Type: cross Abstract: The decentralization of modern energy systems is transforming consumers into prosumers who continuously exchange data with aggregators, peers, and mar

agentsarxiv-cs-ai

Your Students Don't Use LLMs Like You Wish They Did

arXiv:2604.23486v1 Announce Type: new Abstract: Educational NLP systems are typically evaluated using engagement metrics and satisfaction surveys, which are at best a proxy for meeting pedagogical goa

safetyarxiv-cs-cl

Local Ai

3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale

arXiv:2511.13211v2 Announce Type: replace Abstract: Despite recent advancements in 3D-text cross-modal alignment, existing state-of-the-art methods still struggle to align fine-grained textual semanti

local-aiarxiv-cs-cv

AgentBound: Securing Execution Boundaries of AI Agents

arXiv:2510.21236v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have evolved into AI agents that interact with external tools and environments to perform complex tasks. The Mode

safetyarxiv-cs-ai

Agentic Inequality

arXiv:2510.16853v3 Announce Type: replace-cross Abstract: Autonomous AI agents capable of complex planning and action mark a shift beyond today's generative tools. As these systems enter political and

agentsarxiv-cs-ai

AgentSearchBench: A Benchmark for AI Agent Search in the Wild

arXiv:2604.22436v1 Announce Type: new Abstract: The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable a

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting

arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett

tutorialsarxiv-cs-lg

DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysis

arXiv:2601.23022v3 Announce Type: replace Abstract: Aspect-Based Sentiment Analysis (ABSA) focuses on extracting sentiment at a fine-grained aspect level and has been widely applied across real-world

DM^3-Nav: Decentralized Multi-Agent Multimodal Multi-Object Semantic Navigation

arXiv:2604.22014v1 Announce Type: cross Abstract: We present DM^3-Nav, a fully decentralized multi-agent semantic navigation system supporting multimodal open-vocabulary goal specification and multi-o

agentsarxiv-cs-ro

EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms

arXiv:2604.22036v1 Announce Type: cross Abstract: This paper introduces EgoMAGIC (Medical Assistance, Guidance, Instruction, and Correction), an egocentric medical activity dataset collected as part o

Local Ai

How Supply Chain Dependencies Complicate Bias Measurement and Accountability Attribution in AI Hiring Applications

arXiv:2604.22679v1 Announce Type: cross Abstract: The increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses includin

local-aiarxiv-cs-ai

Applications

ICPR 2026 Competition on Low-Resolution License Plate Recognition

arXiv:2604.22506v1 Announce Type: new Abstract: Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compr

applicationsarxiv-cs-cv

Language Specific Knowledge: Do Models Know Better in X than in English?

arXiv:2505.14990v3 Announce Type: replace Abstract: Often, multilingual language models are trained with the objective to map semantically similar content (in different languages) in the same latent s

MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection

model-releasesarxiv-cs-lg

arXiv:2602.09329v2 Announce Type: replace Abstract: Quality benchmarks are essential for fairly and accurately tracking scientific progress and enabling practitioners to make informed methodological c

PSI: A Benchmark for Human Interpretation and Response in Traffic Interactions

arXiv:2112.02604v3 Announce Type: replace-cross Abstract: Accurately modeling pedestrian intention and understanding driver decision-making processes are critical for the development of safe and socia

Recent Advances in Multi-Agent Human Trajectory Prediction: A Comprehensive Review

arXiv:2506.14831v3 Announce Type: replace Abstract: With the emergence of powerful data-driven methods in human trajectory prediction (HTP), gaining a finer understanding of multi-agent interactions l

Applications

Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities

arXiv:2604.22749v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, in

applicationsarxiv-cs-cl

Applications

Segment Any-Quality Images with Generative Latent Space Enhancement

arXiv:2503.12507v3 Announce Type: replace Abstract: Despite their success, Segment Anything Models (SAMs) experience significant performance drops on severely degraded, low-quality images, limiting th

applicationsarxiv-cs-cv