Search: “evaluation”

Item Response Scaling Laws: A Measurement Theory Approach for Efficient and Generalizable Neural Scaling Estimation

arXiv:2606.07616v1 Announce Type: cross Abstract: Scaling laws provide a fundamental framework for understanding the performance of Language Models (LMs), yet deriving them requires prohibitively expe

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

KITE: A Tri-Modal Transformer Integrating Text, Images, and Knowledge Graphs for Fake News Detection

DGX agent

arXiv:2606.07651v1 Announce Type: cross Abstract: Traditional fake news detection methods are falling behind as multimodal misinformation grows more advanced, seamlessly blending deceptive text, manip

model-releasesarxiv-cs-cv

9 Jun 2026

Knowledge-Inclusive Adaptive Physics-Informed Neural Network for Microbial Interaction Modelling

arXiv:2606.07686v1 Announce Type: cross Abstract: Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods. Beyond equations, knowled

LAEI: Layered Autonomous Edge Intelligence Framework for Robust UAV Swarm Operations

arXiv:2606.09099v1 Announce Type: new Abstract: Autonomous UAV swarms require scalable coordination mechanisms that maintain mission performance under limited communication, environmental uncertainty,

safetyarxiv-cs-ro

Lattice: A Confidence-Gated Hybrid System for Uncertainty-Aware Sequential Prediction with Behavioral Archetypes

arXiv:2601.15423v2 Announce Type: replace Abstract: We introduce Lattice, a hybrid sequential prediction system that conditionally activates learned behavioral structure using binary confidence gating

applicationsarxiv-cs-lg

Layer-wise Derivative Controlled Networks Achieve Competitive Accuracy and Gradient Stability Across Data Regimes

arXiv:2606.07908v1 Announce Type: new Abstract: Derivative-controlled networks based on ChainzRule (CR) combine cubic polynomial layers with a lightweight forward-mode per-layer Jacobian penalty (DREG

safetyarxiv-cs-lg

LCAM: A Framework for Diagnosing Interactional Alignment Failures in Con-versational AI

arXiv:2606.08131v1 Announce Type: cross Abstract: Conversational AI is increasingly used for advice, interpretation, reassurance, and decision support in contexts where users may be vulnerable, uncert

Learning from Human Driving: A Human-in-the-Loop Online Behavior Cloning Framework for Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.08170v1 Announce Type: new Abstract: With the evolution of large foundation models (LFMs), data-driven autonomous driving has made significant strides. However, existing paradigms still fac

Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction

arXiv:2606.08751v1 Announce Type: new Abstract: Accurate quantification and uptake measurement in PET are critical for assessing disease progression and supporting clinical decision-making. While high

local-aiarxiv-cs-cv

LFNO: Bridging Laplace and Fourier via Transient-Steady Decomposition

arXiv:2606.07601v1 Announce Type: cross Abstract: We introduce the Laplace-Fourier Neural Operator (LFNO), a unified framework for modeling dynamical systems across transient and steady-state regimes

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines

arXiv:2606.09489v1 Announce Type: new Abstract: Objective: Conformance checking in healthcare seeks to assess whether patient care pathways adhere to clinical guidelines. However, its practical applic

applicationsarxiv-cs-ai

Lost in the Flow with Code Talkers: Unveiling the Instruction-Tuning Tax of Large Language Models in Code Tasks

arXiv:2606.08676v1 Announce Type: cross Abstract: AI coding assistants have significantly improved developer productivity by automatically suggesting code that aligns with user intent, and many of the

Machine-Learning Emulation of Satellite Greenhouse Gas Retrievals: Stability over Time

arXiv:2606.09313v1 Announce Type: new Abstract: Retrieval algorithms are used to estimate atmospheric concentrations of greenhouse gases (GHGs), such as carbon dioxide (CO2) and methane (CH4), by solv

researcharxiv-cs-lg

MedVision: Benchmarking Quantitative Medical Image Analysis

arXiv:2511.18676v2 Announce Type: replace-cross Abstract: Current vision-language models (VLMs) in medicine are primarily designed for categorical question answering (e.g., 'Is this normal or abnormal

MEnvAgent: Scalable Polyglot Environment Construction for Verifiable Software Engineering

arXiv:2601.22859v3 Announce Type: replace-cross Abstract: The evolution of Large Language Model (LLM) agents for software engineering (SWE) is constrained by the scarcity of verifiable datasets, a bot

Minibatch Selection via Partition Matroid Constrained Gradient Matching

arXiv:2606.07954v1 Announce Type: cross Abstract: Training large language models (LLMs) on heterogeneous data requires selecting minibatches that balance convergence speed with coverage across domains

Minimal Solvers for Full-DoF Motion Estimation from Asynchronous Differential SfM

arXiv:2606.09218v1 Announce Type: new Abstract: As a bio-inspired intelligent sensor, event cameras have introduced a new paradigm in the intelligent perception of spatiotemporal information and visua

applicationsarxiv-cs-cv

Agents

MinNav: Minimalist Navigation Using Optical Flow For Active Tiny Aerial Robots

arXiv:2606.07813v1 Announce Type: cross Abstract: Navigation using a monocular camera is pivotal for autonomous operation on tiny aerial robots due to their perfect balance of versatility, cost and ac

agentsarxiv-cs-cv

MIRAGE: Metadata-Integrated Repository Analysis and Guided Enhancement for MSR Datasets

arXiv:2606.07611v1 Announce Type: cross Abstract: This paper proposes an improved approach to the analysis of Mining Software Repositories (MSR) datasets via metadata enrichment, FAIRness assessment,

MMR-GRPO: Accelerating GRPO-Style Training through Diversity-Aware Reward Reweighting

arXiv:2601.09085v2 Announce Type: replace-cross Abstract: Group Relative Policy Optimization (GRPO) has become a standard approach for training mathematical reasoning models; however, its reliance on

Tutorials

Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

arXiv:2601.21149v3 Announce Type: replace-cross Abstract: Recent progress in geospatial foundation models highlights the importance of learning general-purpose representations for real-world locations

tutorialsarxiv-cs-ai

Model Multiplicity for Adversarial Detection in Small Language Model Training on Edge Devices

arXiv:2606.07857v1 Announce Type: cross Abstract: The rise of edge-based machine learning has enabled distributed adaptation of language models across mobile and IoT devices, offering privacy preserva

Modeling Stochastic Conditional Dynamics from Sparse Observations via Kernel-Stabilized Flow Matching

arXiv:2411.08314v5 Announce Type: replace Abstract: Learning to transform conditional probability densities over time is a fundamental challenge spanning probabilistic modeling and the natural science

applicationsarxiv-cs-lg

MS-COOT: Comparing Morse-Smale Complexes with Co-Optimal Transport

arXiv:2606.08258v1 Announce Type: cross Abstract: Understanding and comparing structures in scalar fields is a central challenge in scientific visualization, with applications ranging from feature ana

researcharxiv-cs-cv

Multi-Armed Bandits with Arriving Arms: Sequential Screening, Dynamic Regret, and Sublinear Guarantees

model-releasesarxiv-cs-lg

arXiv:2606.09002v1 Announce Type: cross Abstract: We study a stochastic multi-armed bandit problem in which the set of available arms expands over time. This setting arises in sequential experimentati

Multi-planar 2D-U-Net Segmentation of 3D-CT Abdominal Organs augmented by Spatial Occurrence Maps

arXiv:2606.07717v1 Announce Type: cross Abstract: This work proposes a lightweight 2D-U-Net-based framework for segmenting five abdominal organs in large field-of-view 3D CT scans. The method combines

Multi-resolution Enhancement for Full Spectrum Neural Representations

arXiv:2509.15494v2 Announce Type: replace Abstract: Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-based representations increasingly intractable. Imp

researcharxiv-cs-lg

Muon Learns More Robust and Transferable Features than Adam

arXiv:2606.09658v1 Announce Type: cross Abstract: Muon has recently emerged as a state-of-the-art optimizer for pretraining Large Language Models (LLMs) and vision classifiers. Despite its efficiency

Need We Teach Foundation Models What is a Generative Image? Gradient-Free Generative Artifact Detection via Analytic Spectral Adaptation

arXiv:2606.07660v1 Announce Type: new Abstract: Adapting foundation models to detect generative artifacts via gradient-based updates compromises their intrinsic representations. Under optimization on

local-aiarxiv-cs-cv

Neuro-Symbolic Injection of LTLf Constraints in Autoregressive Reinforcement Learning Policies

arXiv:2606.08312v1 Announce Type: new Abstract: In this work we study offline reinforcement learning (RL) under temporally extended task constraints expressed in Linear Temporal Logic over finite trac

NeuroAlign: Hierarchical Multimodal Fusion of Dynamic and Structural Neuroimaging for MCI Analysis

arXiv:2606.07635v1 Announce Type: cross Abstract: Multimodal neuroimaging fusion of functional MRI (fMRI) and diffusion tensor imaging (DTI) provides complementary information for cognitive impairment

NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts

model-releasesarxiv-cs-cv

arXiv:2606.08535v1 Announce Type: new Abstract: Remote sensing applications for environmental monitoring and disaster management are frequently constrained by a spatial--temporal trade-off: imagery wi

Now You (Still) See Me: Detecting Evasive Steganographic Payloads in LLMs

model-releasesarxiv-cs-lg

arXiv:2606.09411v1 Announce Type: cross Abstract: Large language models can be fine-tuned to encode prompt-borne secrets into fluent, seemingly benign outputs. This creates a steganographic exfiltrati

Observation-driven correction of numerical weather prediction for marine winds

arXiv:2512.03606v2 Announce Type: replace Abstract: Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observati

local-aiarxiv-cs-lg

omega-EVA: Envision, Verify, and Act with Latent Interactive World Models

arXiv:2606.09457v1 Announce Type: new Abstract: Embodied policies typically map current observations directly to actions, leaving candidate-action consequences implicit. World models provide predictiv

safetyarxiv-cs-ro

OmniGameArena: A Unified UE5 Benchmark for VLM Game Agents with Improvement Dynamics

arXiv:2606.09826v1 Announce Type: cross Abstract: Vision-language model (VLM) agents are increasingly deployed in interactive game environments. Yet game benchmarks for VLM agents typically report a s

OmniTryOn: Video Try-On Anything at Once!

model-releasesarxiv-cs-cv

arXiv:2606.08514v1 Announce Type: new Abstract: Although video virtual try-on (VVT) has achieved significant progress, existing methods still exhibit two fundamental limitations: first, they are restr

On solving symmetric multi-type orthogonal non-negative matrix tri-factorization problem

arXiv:2606.08291v1 Announce Type: new Abstract: We study the symmetric multi-type orthogonal non-negative matrix tri-factorization problem, where several symmetric non-negative matrices are simultaneo

researcharxiv-cs-lg

Online Learning for Supervisory Switching Control

arXiv:2603.14762v3 Announce Type: replace-cross Abstract: We study supervisory switching control for partially-observed linear dynamical systems. The objective is to identify and deploy a suitable con

applicationsarxiv-cs-lg

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework

arXiv:2606.08574v1 Announce Type: cross Abstract: Data pruning (DP), as an oft-stated strategy to alleviate heavy training burdens, reduces the volume of training samples according to a well-defined p

safetyarxiv-cs-cv

OSMGraphCLIP: Learning Global Location Representations from OpenStreetMap Graphs

arXiv:2606.08046v1 Announce Type: new Abstract: We present OSMGraphCLIP, a CLIP-style geospatial representation model that learns global location embeddings from freely available OpenStreetMap (OSM) d

local-aiarxiv-cs-ai

Outage Detection in Self-Healing Smart Grids Using Reinforcement Learning with Spectral Graph Neural Networks

arXiv:2606.07583v1 Announce Type: cross Abstract: Self-healing smart grids can quickly adjust their network configuration during outages to minimize power disruptions. During an outage, several action

Oversight Has a Capacity: Calibrating Agent Guards to a Subjective, Fatiguing Human

arXiv:2606.08919v1 Announce Type: new Abstract: As LLM agents begin to take real, irreversible actions (shell commands, file edits, deploys), the standard safety pattern is a human-in-the-loop approva

pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis

arXiv:2511.00934v2 Announce Type: replace-cross Abstract: Signal Temporal Logic (STL) is an expressive language for specifying behaviors of dynamical systems from continuous signals. However, a limita

researcharxiv-cs-ro

PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow

arXiv:2606.07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patc

Payoff scaling shapes cooperation in LLM agents across languages

arXiv:2601.19082v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users. Whether they coo

PereStruct: Multimodal Semantic Assembly for Robust Historical Document Parsing

model-releasesarxiv-cs-cv

arXiv:2606.07661v1 Announce Type: new Abstract: Parsing historical documents with complex, non-standard layouts remains a fundamental bottleneck in large-scale archival digitization. Unlike modern typ

Personalized and Robust Proactive Robot Assistance with Uncertainty-Guided LLM Reasoning

arXiv:2606.08458v1 Announce Type: new Abstract: Proactive robot assistance in household environments requires accurate prediction of human activities and object usage under dynamic and noisy condition

applicationsarxiv-cs-ro