AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,533 papers
Software issue resolution task aims to address real-world issues in software repositories based on natural language descriptions provided by users, representing a key aspect of software maintenance. With the rapid development of large language models (LLMs) in reasoning and generative capabilities, LLM-based approaches...
This paper examines whether advanced large language models operating under enhanced deliberative regimes, here termed Reasoning Language Models (RLMs), possess minds under an explicitly defined functional account. We develop an operational definition informed by Newell’s account of cognitive organization and Gärdenfors...
Large Language Models (LLMs) have achieved substantial progress in solving complex mathematical problems, yet they often fail to exploit the potential value embedded in their own mistakes. Existing methods either apply coarse-grained corrections or rely on costly self-reflection, overlooking valid reasoning steps and i...
Research on Artificial Intelligence (AI) and the circular economy (CE) has largely examined how AI can improve circular operations. Much less attention has been paid to AI tools widely used to understand and reason about the CE, particularly large language models (LLMs) such as ChatGPT. Researchers, practitioners, st...
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This paper examines whether advanced large language models operating under enhanced deliberative regimes, here termed Reasoning Language Models (RLMs), possess minds under an explicitly defined functional account. We develop an operational definition informed by Newell’s account of cognitive organization and Gärdenfors...
The explicit corrections to the k-omega SST turbulence model presented in the paper Toward non-regressing turbulence closures from large language models: explicit corrections to SST tested on unseen flows (C. Charalampous, submitted to Physics of Fluids), the OpenFOAM v2312 library that evaluates them, the evaluation c...
Large Language Models (LLMs) are increasingly used to generate multimodal data for building corpora or simulating synthetic behaviours. A key challenge remains the evaluation of generated data. Comparison with real multimodal human interactions may help address this issue, but unified representations and evaluation fra...
Abstract Large language models generate text token by token, without committing in advance to what a complete answer must contain. This makes them fluent but structurally unreliable: required elements may be omitted, constraints may be ignored, and unsupported claims may appear with unwarranted confidence. Retrieval an...
Study summary A frontier large language model (Claude Opus 4.8, model identifier claude-opus-4-8, Anthropic) was tested against the revised Geneva score for pulmonary embolism using simulated patient profiles. Two tasks were run. Task 1, weight elicitation. The model was asked to assign numeric weights to the component...
Speech neuroprosthesis systems decode intended speech from neural activity in the absence of audible output, offering a path to restoring communication for individuals with speech-impairing conditions. Current approaches decode predominantly from motor cortical areas, discarding others—such as area 44, part of Broca’s...
While Large Language Models are increasingly embedded within long-horizon Human-AI interactions, they are typically evaluated as stateless systems governed by rigid safety alignments. This study introduces blinded Big-5 psychometric telemetry for quantifying behavioral continuity in extended Human-AI interactions and a...
Large language models (LLMs) can predict interpersonal attraction from conversation transcripts, but it remains unclear what a speech predictor can add beyond transcript-only LLM prediction. Using Japanese speed-dating conversations, we combine predictions from a transcript-only LLM and a supervised speech predictor to...
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