Search: “evaluation”

Positional Encoding in Transformer-Based Time Series Models: A Survey

arXiv:2502.12370v3 Announce Type: replace Abstract: Recent advancements in transformer-based models have greatly improved time series analysis, providing robust solutions for tasks such as forecasting

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Practical validation of synthetic pre-crash scenarios

DGX agent

arXiv:2605.04564v1 Announce Type: new Abstract: The representativeness of synthetic pre-crash scenarios is crucial for assessing the safety impact of Driving Automation Systems through virtual simulat

safetyarxiv-cs-ro

7 May 2026

Privacy-Preserving Empathy Detection in Video Interactions

model-releasesarxiv-cs-cv

arXiv:2504.10808v3 Announce Type: replace Abstract: Detecting empathy from video interactions has emerging applications, yet raw videos that could be used for training AI models are rarely available d

Probabilistic Classification and Uncertainty Quantification of Sahara Desert Climate Using Feedforward Neural Networks

arXiv:2605.04286v1 Announce Type: new Abstract: Climate classification plays a vital role in agricultural planning, hydrological studies, and climate science. One of the most widely used systems for c

Provable Non-Convex Euclidean Distance Matrix Completion: Geometry, Reconstruction, and Robustness

arXiv:2508.00091v3 Announce Type: replace-cross Abstract: The problem of recovering the configuration of points from their partial pairwise distances, referred to as the Euclidean Distance Matrix Comp

Applications

Proximal Projection for Doubly Sparse Regularized Models

arXiv:2605.05093v1 Announce Type: cross Abstract: Regularization is often used in high-dimensional regression settings to generate a sparse model, which can save tremendous computing resources and ide

applicationsarxiv-cs-lg

Hardware

Quadrature-TreeSHAP: Depth-Independent TreeSHAP and Shapley Interactions

arXiv:2605.04497v1 Announce Type: new Abstract: Shapley values are a standard tool for explaining predictions of tree ensembles, with Path-Dependent SHAP being the most widely used variant. Despite su

hardwarearxiv-cs-lg

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design

arXiv:2409.09183v2 Announce Type: replace Abstract: Synthesizable molecular design (also known as synthesizable molecular optimization) is a fundamental problem in drug discovery, and involves designi

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models

arXiv:2605.03426v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have broad potential in privacy-sensitive domains such as healthcare and finance, yet strict data-sharing constraints rend

Reward-Guided Semantic Evolution for Test-time Adaptive Object Detection

arXiv:2605.04531v1 Announce Type: new Abstract: Open-vocabulary object detection with vision-language models (VLMs) such as Grounding DINO suffers from performance degradation under test-time distribu

researcharxiv-cs-cv

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization

arXiv:2605.04539v1 Announce Type: new Abstract: Direct Preference Optimization (DPO), the efficient alternative to PPO-based RLHF, falls short on knowledge-intensive generation: standard preference si

Agents

RouteFormer: A Transformer-Based Routing Framework for Autonomous Vehicles

arXiv:2504.05407v2 Announce Type: replace-cross Abstract: Autonomous surveillance missions in Internet of Things (IoT) networks often involve solving NP-hard combinatorial optimization problems to ens

agentsarxiv-cs-lg

Self-Attention as Transport: Limits of Symmetric Spectral Diagnostics

arXiv:2605.04893v1 Announce Type: cross Abstract: Large language models hallucinate in predictable ways: attention routing fails by over-concentrating on a narrow set of positions, or by spreading so

Hardware

SemiConLens: Visual Analytics for 2D Semiconductor Discovery

arXiv:2605.04067v1 Announce Type: cross Abstract: The past few years have witnessed vibrant efforts in discovering new two-dimensional (2D) semiconductor materials from both academia and the industry,

hardwarearxiv-cs-lg

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

Applications

Shape2Animal: Creative Animal Generation from Natural Silhouettes

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

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

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

Agents

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

agentsarxiv-cs-ai

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

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

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

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

safetyarxiv-cs-cv

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

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

safetyarxiv-cs-cv

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

safetyarxiv-cs-cv

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