2024 SEMEVAL SemEval 2024

OctavianB at SemEval-2024 Task 6: An exploration of humanlike qualities of hallucinated LLM texts

Abstract

AbstractThe tested method for detection involves utilizing models, trained for differentiating machine-generated text, in order to distinguish between regular and hallucinated sequences. The hypothesis under investigation is that the patterns learned in pretraining will be transferable to the task at hand. The rationale is as follows: the training data of the model is human-written text, therefore deviations from the training set could be detected in this manner.A second method has been added post competition as a further exploration of the dataset involving using the loss of the generation as determined by a pretrained LLM.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio