Search: “evaluation”

SC-Taxo: Hierarchical Taxonomy Generation under Semantic Consistency Constraints using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.00620v1 Announce Type: new Abstract: Scientific literature is expanding at an unprecedented pace, making it increasingly challenging to efficiently organize and access domain knowledge. A h

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification

DGX agent

arXiv:2605.00218v1 Announce Type: cross Abstract: Mobile remote identity verification (RIdV) systems are exposed to attacks that manipulate or replace the facial video stream, including presentation a

model-releasesarxiv-cs-lg

4 May 2026

Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution

arXiv:2605.00056v1 Announce Type: new Abstract: Groundwater in the Densu Basin is increasingly threatened by heavy metal contamination, but conventional methods fail to capture the statistical complex

Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech

arXiv:2603.15988v2 Announce Type: replace-cross Abstract: Dysarthric speech quality assessment (DSQA) is critical for clinical diagnostics and inclusive speech technologies. However, subjective evalua

Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation

arXiv:2605.00318v1 Announce Type: new Abstract: Tabular documents such as CSV and Excel files are widely used in enterprise data pipelines, yet existing chunking strategies for retrieval-augmented gen

applicationsarxiv-cs-cl

Sure About That Line? Approaching Confidence-Based, Real-Time Line Assignment in Reading Gaze Data

arXiv:2605.00033v1 Announce Type: cross Abstract: Remote and webcam-based eye tracking in multi-line reading suffers from various noise factors and layout ambiguity, precisely where real-time reading

SynQuE: Estimating Synthetic Dataset Quality Without Annotations

arXiv:2511.03928v5 Announce Type: replace Abstract: We introduce and formalize the Synthetic Dataset Quality Estimation (SynQuE) problem: ranking synthetic datasets by their expected real-world task p

applicationsarxiv-cs-lg

Task-Conditioned Uncertainty Costmaps for Legged Locomotion

arXiv:2605.00261v1 Announce Type: new Abstract: Legged robots maintain dynamic feasibility through multicontact interactions with terrain. Learned foothold prediction can provide feasibility-aware cos

applicationsarxiv-cs-ro

Temporal Data Requirement for Predicting Unplanned Hospital Readmissions

arXiv:2605.00738v1 Announce Type: new Abstract: With the proliferation of Electronic Health Records (EHRs), a critical challenge in building predictive models is determining the optimal historical dat

Local Ai

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge

arXiv:2605.00536v1 Announce Type: cross Abstract: Scaling laws for Large Language Models (LLMs) establish that model quality improves with computational scale, yet edge deployment imposes strict const

local-aiarxiv-cs-lg

Thinking with Geometry: Active Geometry Integration for Spatial Reasoning

arXiv:2602.06037v4 Announce Type: replace Abstract: Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However

agentsarxiv-cs-cv

TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning

arXiv:2605.00015v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) advance generalization and data efficiency in time series forecasting by unified large-scale pretraining. But TS

applicationsarxiv-cs-cv

Local Ai

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

local-aiarxiv-cs-lg

TURBOTEST: Learning When Less is Enough through Early Termination of Internet Speed Tests

model-releasesarxiv-cs-lg

arXiv:2510.21141v2 Announce Type: replace-cross Abstract: Internet speed tests are indispensable for users, ISPs, and policymakers, but their static flooding-based design imposes growing costs: a sing

Understanding Cognitive States from Head & Hand Motion Data

arXiv:2509.24255v2 Announce Type: replace-cross Abstract: As virtual reality (VR) becomes widespread, head and hand motion data captured by consumer systems has become substantially more common. Howev

ViLegalNLI: Natural Language Inference for Vietnamese Legal Texts

model-releasesarxiv-cs-cl

arXiv:2605.00116v1 Announce Type: new Abstract: In this article, we introduce ViLegalNLI, the first large-scale Vietnamese Natural Language Inference (NLI) dataset specifically constructed for the leg

VLAs are Confined yet Capable of Generalizing to Novel Instructions

model-releasesarxiv-cs-ro

arXiv:2505.03500v5 Announce Type: replace Abstract: Vision-language-action models (VLAs) often achieve high performance on demonstrated tasks but struggle significantly when required to extrapolate, c

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks

arXiv:2605.00725v1 Announce Type: new Abstract: Combinatorial complexes have unified set-based (e.g., graphs, hypergraphs) and part-whole (e.g., simplicial, cellular complexes) structures into a commo

applicationsarxiv-cs-lg

WildfireVLM: AI-powered Analysis for Early Wildfire Detection and Risk Assessment Using Satellite Imagery

arXiv:2602.13305v2 Announce Type: replace Abstract: Wildfires are a growing threat to ecosystems, human lives, and infrastructure, with their frequency and intensity rising due to climate change and h

3D-ReGen: A Unified 3D Geometry Regeneration Framework

arXiv:2604.28134v1 Announce Type: new Abstract: We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting te

A Gated Hybrid Contrastive Collaborative Filtering Recommendation

arXiv:2604.27117v1 Announce Type: cross Abstract: Recommender systems increasingly incorporate textual reviews to enrich user and item representations. However, most review-aware models remain optimiz

researcharxiv-cs-ai

Tutorials

A generalised pre-training strategy for deep learning networks in semantic segmentation of remotely sensed images

arXiv:2604.27704v1 Announce Type: new Abstract: In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tune

tutorialsarxiv-cs-cv

A Novel Computational Framework for Causal Inference: Tree-Based Discretization with ILP-Based Matching

arXiv:2604.27307v1 Announce Type: cross Abstract: Causal inference is essential for data-driven decision-making, as it aims to uncover causal relationships from observational data. However, identifyin

ActiNet: An Open-Source Tool for Activity Intensity Classification of Wrist-Worn Accelerometry Using Self-Supervised Deep Learning

arXiv:2510.01712v2 Announce Type: replace Abstract: The use of accurate and reliable open-source human activity recognition (HAR) models on passively collected wrist-accelerometer data is essential in

Activation Function Design Sustains Plasticity in Continual Learning

arXiv:2509.22562v4 Announce Type: replace-cross Abstract: In independent, identically distributed (i.i.d.) training regimes, activation functions have been benchmarked extensively, and their differenc

researcharxiv-cs-ai

Adaptive Nonlinear MPC for Trajectory Tracking of An Overactuated Tiltrotor Hexacopter

arXiv:2211.06762v2 Announce Type: replace Abstract: Omnidirectional micro aerial vehicles (OMAVs) are more capable of doing environmentally interactive tasks due to their ability to exert full wrenche

researcharxiv-cs-ro

Addressing the Reality Gap: A Three-Tension Framework for Agentic AI Adoption

arXiv:2604.27245v1 Announce Type: cross Abstract: Generative AI has rapidly entered education through free consumer tools, outpacing the ability of schools and universities to respond. Now a new wave

AEGIS: Authentic Edge Growth In Sparsity for Link Prediction in Edge-Sparse Bipartite Knowledge Graphs

arXiv:2509.22017v4 Announce Type: replace Abstract: Bipartite knowledge graphs in niche domains are typically data-poor and edge-sparse, which hinders link prediction. We introduce AEGIS (Authentic Ed

safetyarxiv-cs-lg

AG-TAL: Anatomically-Guided Topology-Aware Loss for Multiclass Segmentation of the Circle of Willis Using Large-Scale Multi-Center Datasets

arXiv:2604.27357v1 Announce Type: cross Abstract: Accurate multiclass segmentation of the Circle of Willis (CoW) is essential for neurovascular disease management but remains challenging due to comple

AgentEconomist: An End-to-end Agentic System Translating Economic Intuitions into Executable Computational Experiments

arXiv:2604.27725v1 Announce Type: cross Abstract: A long-standing challenge in economics lies not in the lack of intuition, but in the difficulty of translating intuitive insights into verifiable rese

agentsarxiv-cs-ai

Agentic Education: Using Claude Code to Teach Claude Code

arXiv:2604.17460v2 Announce Type: replace-cross Abstract: AI coding assistants have proliferated rapidly, yet structured pedagogical frameworks for learning these tools remain scarce. Developers face

AI Models for Depressive Disorder Detection and Diagnosis: A Review

arXiv:2508.12022v2 Announce Type: replace Abstract: Major Depressive Disorder is one of the leading causes of disability worldwide, yet its diagnosis still depends largely on subjective clinical asses

An adaptive wavelet-based PINN for problems with localized high-magnitude source

arXiv:2604.28180v1 Announce Type: new Abstract: In recent years, physics-informed neural networks (PINNs) have gained significant attention for solving differential equations, although they suffer fro

safetyarxiv-cs-lg

An Experimental Modular Instrument With a Haptic Feedback Framework for Robotic Surgery Training

arXiv:2604.27385v1 Announce Type: new Abstract: Robotic-assisted surgery offers significant clinical advantages but largely eliminates direct haptic feedback, increasing the risk of excessive tool-tis

researcharxiv-cs-ro

ANCORA: Learning to Question via Manifold-Anchored Self-Play for Verifiable Reasoning

arXiv:2604.27644v1 Announce Type: cross Abstract: We propose a paradigm shift from learning to answer to learning to question: can a language model generate verifiable problems, solve them, and turn t

Automated Detection of Mutual Gaze and Joint Attention in Dual-Camera Settings via Dual-Stream Transformers

arXiv:2604.27105v1 Announce Type: new Abstract: Analyzing mutual gaze (MG) and joint attention (JA) is critical in developmental psychology but traditionally relies on labor-intensive manual coding. A

Automatic Causal Fairness Analysis with LLM-Generated Reporting

arXiv:2604.27011v1 Announce Type: cross Abstract: AutoML, intended as the process of automating the application of machine learning to real-world problems, is a key step for AI popularisation. Most Au

AutoREC: A software platform for developing reinforcement learning agents for equivalent circuit model generation from electrochemical impedance spectroscopy data

arXiv:2604.27266v1 Announce Type: new Abstract: This paper introduces AutoREC, an open-source Python package for developing reinforcement learning (RL) agents to automatically generate equivalent circ

agentsarxiv-cs-lg

Autoregressive Synthesis of Sparse and Semi-Structured Mixed-Type Data

model-releasesarxiv-cs-lg

arXiv:2603.01444v2 Announce Type: replace Abstract: Synthetic data generation is an important capability for privacy-preserving data sharing, system benchmarking and test data provisioning. For mixed-

AutoSP: Unlocking Long-Context LLM Training Via Compiler-Based Sequence Parallelism

model-releasesarxiv-cs-lg

arXiv:2604.27089v1 Announce Type: new Abstract: Large-language-models (LLMs) demonstrate enormous utility in long-context tasks which require processing prompts that consist of tens to hundreds of tho

AutoSurfer -- Teaching Web Agents through Comprehensive Surfing, Learning, and Modeling

arXiv:2604.27253v1 Announce Type: new Abstract: Recent advances in multimodal large language models (LLMs) have revolutionized web agents that can automate complex tasks on websites. However, their ac

Hardware

Benchmarking Deep Learning Models for Object Detection on Edge Computing Devices

arXiv:2409.16808v1 Announce Type: cross Abstract: Modern applications, such as autonomous vehicles, require deploying deep learning algorithms on resource-constrained edge devices for real-time image

hardwarearxiv-cs-lg

Beyond Pixel Fidelity: Minimizing Perceptual Distortion and Color Bias in Night Photography Rendering

arXiv:2604.28136v1 Announce Type: new Abstract: Night Photography Rendering (NPR) poses a significant challenge due to the extreme contrast between dark and illuminated areas in scenes, stemming from

safetyarxiv-cs-cv

Calibrating Attribution Proxies for Reward Allocation in Participatory Weather Sensing

arXiv:2604.27944v1 Announce Type: new Abstract: Large-scale IoT weather sensing networks require incentive mechanisms to sustain participation, yet determining how much value individual data contribut

Can Large Language Models Implement Agent-Based Models? An ODD-based Replication Study

arXiv:2602.10140v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can now synthesize non-trivial executable code from textual descriptions, raising an important question: can LLMs

CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting

arXiv:2604.27840v1 Announce Type: cross Abstract: Recently, large language models (LLMs) have shown great promise in time series forecasting. However, most existing LLM-based forecasting methods still

agentsarxiv-cs-ai

Characterizing the Consistency of the Emergent Misalignment Persona

arXiv:2604.28082v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) on narrowly misaligned data generalizes to broadly misaligned behavior, a phenomenon termed emergent misalignme

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model

arXiv:2506.09110v3 Announce Type: replace Abstract: Electroencephalography (EEG) provides real-time insights into brain activity and supports diverse applications in neuroscience. While EEG foundation