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From Atomic to Agentic: Towards Interpretable Evaluation of LLMs' Agentic Mathematical Capabilities introduces AgenticMathBench (AMB), a benchmark designed t...
WikiSkill is a framework designed to improve how AI agents develop and refine specialized skills.
A Contract-Centered Architecture for Scalable and Manageable Agentic Runtimes proposes a framework to address the coordination challenges of deploying enterp...
Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection introduces a new method called JPGFN to improve how computers i...
BrailleBench is a new benchmark designed to evaluate how well Large Language Models (LLMs) comprehend and generate Braille.
A Multi-Modal AI Framework for Real-Time Queue Prediction, Management and Optimisation in Intelligent Border Control Systems proposes a system to improve bor...
What the paper is about We ask whether large language models (LLMs) can design effective algorithms for well-specified operations research (OR) problems.
Thomson: Continual Learning of Frontier Models for SovereignAI introduces a method for institutions to develop high-performance, private AI models without re...
LAAF: A Layered Accountability Architecture Framework for LLM Applications provides a systematic approach to assigning responsibility when Large Language Mod...
Counterfactual Bias Testing for Application Tracking System presents a methodology for auditing automated hiring tools for demographic bias.
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