Search: “evaluation”

Sentiment Analysis and Customer Satisfaction Prediction on E-Commerce Platforms Based on YouTube Comments Using the XGBoost Algorithm

arXiv:2605.04887v1 Announce Type: new Abstract: The exponential expansion of digital commerce in Indonesia has significantly shifted consumer interactions toward video-centric social networks, particu

Human

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Applications

Shape2Animal: Creative Animal Generation from Natural Silhouettes

DGX agent

arXiv:2506.20616v3 Announce Type: replace Abstract: Humans possess a unique ability to perceive meaningful patterns in ambiguous stimuli, a cognitive phenomenon known as pareidolia. This paper introdu

applicationsarxiv-cs-cv

7 May 2026

SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation

model-releasesarxiv-cs-cv

arXiv:2511.06754v3 Announce Type: replace-cross Abstract: Inspired by how humans reason over discrete objects and their relationships, we explore whether compact object-centric and object-relation rep

Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search

arXiv:2605.04057v1 Announce Type: new Abstract: This paper focuses on a key challenge in Neural Architecture Search (NAS): integrating established architectural knowledge while exploring new designs u

local-aiarxiv-cs-lg

Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting

arXiv:2605.05151v1 Announce Type: new Abstract: Transformer architectures have been widely adopted for time series forecasting, yet whether the representational mechanisms that make them powerful in N

SWAN: Semantic Watermarking with Abstract Meaning Representation

model-releasesarxiv-cs-cl

arXiv:2605.04305v1 Announce Type: new Abstract: We introduce SWAN (Semantic Watermarking with Abstract Meaning Representation), a novel framework that embeds watermark signatures into the semantic str

SymptomAI: Towards a Conversational AI Agent for Everyday Symptom Assessment

arXiv:2605.04012v1 Announce Type: new Abstract: Language models excel at diagnostic assessments on currated medical case-studies and vignettes, performing on par with, or better than, clinical profess

Syn4D: A Multiview Synthetic 4D Dataset

arXiv:2605.05207v1 Announce Type: new Abstract: Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this are

researcharxiv-cs-cv

Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors

model-releasesarxiv-cs-lg

arXiv:2602.00305v2 Announce Type: replace-cross Abstract: LLM-based vulnerability detectors are increasingly deployed in CI/CD security gating, yet their resilience to evasion under syntax- and compil

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding

model-releasesarxiv-cs-cl

arXiv:2605.04962v1 Announce Type: new Abstract: Foundation models have established unified representations for natural language processing, yet this paradigm remains largely unexplored for tabular dat

TCM-Serve: Modality-aware Scheduling for Multimodal Large Language Model Inference

arXiv:2603.26498v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) power platforms like ChatGPT, Gemini, and Copilot, enabling richer interactions with text, images, an

Telegraph English: Semantic Prompt Compression via Structured Symbolic Rewriting

model-releasesarxiv-cs-cl

arXiv:2605.04426v1 Announce Type: new Abstract: We introduce Telegraph English (TE), a prompt-compression protocol that rewrites natural language into a symbol-rich, formally-structured dialect. Where

Temporal Structure Matters for Efficient Test-Time Adaptation in Wearable Human Activity Recognition

arXiv:2605.04617v1 Announce Type: new Abstract: Wearable human activity recognition (WHAR) models often suffer from performance degradation under real-world cross-user distribution shifts. Test-time a

Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?

arXiv:2605.03195v1 Announce Type: new Abstract: Modern coding agents increasingly delegate specialized subtasks to subagents, which are smaller, focused agentic loops that handle narrow responsibiliti

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement

arXiv:2605.05103v1 Announce Type: new Abstract: We introduce the **Concept Field** of a text corpus: a local drift field with pointwise uncertainty, estimated in sentence-embedding space from the delt

local-aiarxiv-cs-cl

Applications

TNStream: Applying Tightest Neighbors to Micro-Clusters to Define Multi-Density Clusters in Streaming Data

arXiv:2505.00359v2 Announce Type: replace Abstract: In data stream clustering, systematic theory of stream clustering algorithms remains relatively scarce. Recently, density-based methods have gained

applicationsarxiv-cs-lg

To Fuse or to Drop? Dual-Path Learning for Resolving Modality Conflicts in Multimodal Emotion Recognition

arXiv:2605.04877v1 Announce Type: cross Abstract: Multimodal emotion recognition (MER) benefits from combining text, audio, and vision, yet standard fusion often fails when modalities conflict. Crucia

safetyarxiv-cs-lg

Toward Human-AI Complementarity Across Diverse Tasks

arXiv:2605.04070v1 Announce Type: cross Abstract: Human-AI complementarity, the idea that combining human and AI judgments can outperform either alone, offers a promising pathway toward robust oversig

Towards Generative Location Awareness for Disaster Response: A Probabilistic Cross-view Geolocalization Approach

arXiv:2512.20056v2 Announce Type: replace-cross Abstract: As Earth's climate changes, it is impacting disasters and extreme weather events across the planet. Record-breaking heat waves, drenching rain

local-aiarxiv-cs-cv

Transformation Categorization Based on Group Decomposition Theory Using Parameter Division

model-releasesarxiv-cs-lg

arXiv:2605.04056v1 Announce Type: new Abstract: Representation learning seeks meaningful sensory representations without supervision and can model aspects of human development. Although many neural ne

Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity

arXiv:2605.04827v1 Announce Type: new Abstract: Label Distribution Learning (LDL) models supervision as an instance-wise probability distribution, enabling fine-grained learning under inherent ambigui

UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning

arXiv:2508.11196v2 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have demonstrated strong generalization in natural image tasks. However, their performance often de

UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization

arXiv:2511.08195v3 Announce Type: replace Abstract: UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing metho

Understanding LoRA as Knowledge Memory: An Empirical Analysis

arXiv:2603.01097v2 Announce Type: replace Abstract: Continuous knowledge updating for pre-trained large language models (LLMs) is increasingly necessary yet remains challenging. Although inference-tim

Tutorials

Velox: Learning Representations of 4D Geometry and Appearance

arXiv:2605.04527v1 Announce Type: new Abstract: We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; c

tutorialsarxiv-cs-cv

Vol-Mark: A Watermark for 3D Medical Volume Data Via Cubic Difference Expansion and Contrastive Learning

arXiv:2605.04705v1 Announce Type: cross Abstract: Today, advances in medical technology extensively utilize 3D volume data for accurate and efficient diagnostics. However, sharing these data across ne

Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging

model-releasesarxiv-cs-cv

arXiv:2605.05161v1 Announce Type: new Abstract: Zero-shot anomaly localisation via vision-language models (VLMs) offers a compelling approach for rare pathology detection, yet its performance is funda

When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data

arXiv:2605.04930v1 Announce Type: new Abstract: Despite theoretical advantages, causal methods for Gene Regulatory Network (GRN) inference from single-cell RNA-seq data consistently fail to match or o

When Engineering Outruns Intelligence: Rethinking Instruction-Guided Navigation

arXiv:2507.20021v3 Announce Type: replace-cross Abstract: Recent ObjectNav systems credit large language models (LLMs) for sizable zero-shot gains, yet it remains unclear how much comes from language

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise

arXiv:2605.05045v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong multimodal performance but remain prone to relation hallucination, which requires accurate reasoning over

6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence

arXiv:2605.01546v1 Announce Type: cross Abstract: Sixth-generation (6G) networks are increasingly envisioned as AI-native infrastructures integrating communication, sensing, and computing into a unifi

A Cellular Doctrine of Morality: Intrinsic Active Precision and the Mind-Reality Overload Dilemma

arXiv:2605.01376v1 Announce Type: new Abstract: Current AI systems, grounded in oversimplified neuroscience, risk eroding the distinction between truth and falsehood. They maximize reward by amplifyin

local-aiarxiv-cs-ai

A Comparison of Traditional Machine Learning Algorithms and LSTM-Based Deep Learning Models for Email Sentiment Analysis

arXiv:2605.03440v1 Announce Type: new Abstract: The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

arXiv:2605.03696v1 Announce Type: new Abstract: The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there ar

A Domain Incremental Continual Learning Benchmark for ICU Time Series Model Transportability

model-releasesarxiv-cs-lg

arXiv:2605.03832v1 Announce Type: new Abstract: In recent years, machine learning has made significant progress in clinical outcome prediction, demonstrating increasingly accurate results. However, th

A Low-Latency Fraud Detection Layer for Detecting Adversarial Interaction Patterns in LLM-Powered Agents

arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the

A Perfectly Truthful Calibration Measure

arXiv:2508.13100v3 Announce Type: replace Abstract: Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quan

A Robust Unsupervised Domain Adaptation Framework for Medical Image Classification Using RKHS-MMD

arXiv:2605.03787v1 Announce Type: new Abstract: Labeling medical images is a major bottleneck in the field of medical imaging, as it requires domain-specific expertise, and it gets further complicated

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

researcharxiv-cs-ai

A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)

arXiv:2605.02249v1 Announce Type: new Abstract: We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent ga

A Target-Free Harmonization Method for MRI

arXiv:2605.01282v1 Announce Type: cross Abstract: In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsist

researcharxiv-cs-ai

A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis

arXiv:2605.02903v1 Announce Type: cross Abstract: In recent years, AI systems in the medical domain have advanced significantly. However, despite outperforming humans, they are rarely used in practice

researcharxiv-cs-cv

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

arXiv:2605.03495v1 Announce Type: new Abstract: We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a

Tools

Adding Benchmaxxer Repellant to the Open ASR Leaderboard

This article discusses the integration of Benchmaxxer Repellant into the Open ASR (Automatic Speech Recognition) Leaderboard, likely a tool or mechanism designed to prevent gaming or manipulation of l

toolshugging-face

Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

arXiv:2603.01486v2 Announce Type: replace Abstract: Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where conte

Applications

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

arXiv:2507.22101v2 Announce Type: replace Abstract: Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sec

applicationsarxiv-cs-cv

AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries

arXiv:2605.01415v1 Announce Type: new Abstract: Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital inten