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Large Language Collider
Let's hope machine learning people don't take naming lessons from astronomers otherwise next we'll be getting Very Large Language Models
@julesh Ludicrously Large Language Model (LLLM)
@julesh It's too late already: https://arxiv.org/abs/2404.16859
arXiv.orgRumour Evaluation with Very Large Language ModelsConversational prompt-engineering-based large language models (LLMs) have enabled targeted control over the output creation, enhancing versatility, adaptability and adhoc retrieval. From another perspective, digital misinformation has reached alarming levels. The anonymity, availability and reach of social media offer fertile ground for rumours to propagate. This work proposes to leverage the advancement of prompting-dependent LLMs to combat misinformation by extending the research efforts of the RumourEval task on its Twitter dataset. To the end, we employ two prompting-based LLM variants (GPT-3.5-turbo and GPT-4) to extend the two RumourEval subtasks: (1) veracity prediction, and (2) stance classification. For veracity prediction, three classifications schemes are experimented per GPT variant. Each scheme is tested in zero-, one- and few-shot settings. Our best results outperform the precedent ones by a substantial margin. For stance classification, prompting-based-approaches show comparable performance to prior results, with no improvement over finetuning methods. Rumour stance subtask is also extended beyond the original setting to allow multiclass classification. All of the generated predictions for both subtasks are equipped with confidence scores determining their trustworthiness degree according to the LLM, and post-hoc justifications for explainability and interpretability purposes. Our primary aim is AI for social good.
@julesh Thankfully, even the physicists haven't reached "yo moma"''s order of magnitude in size
My favourite was OWL, OverWhelmingly Large. Never got built though.
@julesh
Wait till they follow game dev terminology (epically large, legendary large, etc)