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3,656 papers
These findings show that reliable evaluation of LLM-generated code requires validated ground truth, protected tests, and multiple explicitly interpreted measures, and that CodeAssay provides a reproducible basis for evidence-based model evaluation in AI-augmented software development.
Programmable Logic Controllers (PLCs) are central to industrial automation, yet their programming remains largely manual and time-consuming. While Large Language Models (LLMs) excel at general-purpose code generation, their use in industrial control is limited by tight coupling with physical hardware, constrained I/O s...
The first comprehensive benchmarking framework specifically designed to accommodate inter-dataset heterogeneity is presented, finding that well-designed small datasets can match or even surpass the performance of larger benchmarks, suggesting that different metrics are applicable to different datasets/testing scenarios...
A novel committor learning framework grounded in the AlphaFold 3 paradigm is proposed that elucidates how ligand substituents regulate the ratio between distinct binding pathways, offering new perspectives for structure-based drug design.
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The Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein-ligand distances and reconstructs binding poses; and RTMScor...
This paper test representative models regarding their knowledge of Chinese and Japanese Buddhist history on consumer hardware and finds that, in Spring 2026, the Qwen series emerges as a winner for models in the 30B range, while the larger Kimi2.5 models lead in a cloud-based setup.
This study presents the first systematic literature review of research on Estonian Sign Language (EVK) published between 1985 and 2024. Using Okoli's eight-step systematic literature review (SLR) model, we identified and screened 52 sources. Twenty-one were excluded on the basis of predefined criteria, leavi...
This work presents the first complete system for automated six degrees of freedom (6DOF) satellite pose estimation from spatially resolved, ground-based, adaptive optics (AO)-corrected imagery, addressing a key challenge in Space Domain Awareness (SDA). The approach mitigates the need for human labeling by directly reg...
Among the six evaluated model configurations, GPT-5.2 achieved significantly higher agreement with the clinician-derived composite reference than the other tested models for both ASA-PS and CCI in post hoc paired analyses with multiplicity correction.
It is argued that realizing deep learning’s full potential requires not only architectural innovation but also domain-aware representations that encode the statistical ensemble nature of polymers, evaluation protocols aligned with discovery scenarios, and physically grounded inductive biases.
Results align with a diagnostic perspective on chunking: using evidence at a task-appropriate level of granularity can improve grounding, auditability, and answer quality, but the observed patterns should be interpreted within the HotpotQA distractor setting, fixed generator, and tested context budgets.
IT help desks at large organizations face a high volume of recurrent, well-documented user requests that nevertheless require human-written replies, creating a persistent staff workload that is repetitive in content but non-trivial in tone and procedural correctness. We present FroLineR, short for Front-Line Response,...
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