arXiv:2310.18906
공식 코드 · Papers with Code
Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection
원문 초록
This paper reports our submission under the team name `SynthDetectives' to the ALTA 2023 Shared Task. We use a stacking ensemble of Transformers for the task of AI-generated text detection. Our approach is novel in terms of its choice of models in that we use accessible and lightweight models in the ensemble. We show that ensembling the models results in an improved accuracy in comparison with using them individually. Our approach achieves an accuracy score of 0.9555 on the official test data provided by the shared task organisers.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Stress-testing Machine Generated Text Detection: Shifting Language Models Writing Style to Fool Detectors
The Devil is in Fine-tuning and Long-tailed Problems:A New Benchmark for Scene Text Detection
FAID: Fine-grained AI-generated Text Detection using Multi-task Auxiliary and Multi-level Contrastive Learning
Visual Text Processing: A Comprehensive Review and Unified Evaluation
SemiETS: Integrating Spatial and Content Consistencies for Semi-Supervised End-to-end Text Spotting
Short-PHD: Detecting Short LLM-generated Text with Topological Data Analysis After Off-topic Content Insertion
토론
이 논문과 연결된 포럼 글이 아직 없습니다.