arXiv:2306.08116
공식 코드 · Papers with Code
CipherSniffer: Classifying Cipher Types
원문 초록
Ciphers are a powerful tool for encrypting communication. There are many different cipher types, which makes it computationally expensive to solve a cipher using brute force. In this paper, we frame the decryption task as a classification problem. We first create a dataset of transpositions, substitutions, text reversals, word reversals, sentence shifts, and unencrypted text. Then, we evaluate the performance of various tokenizer-model combinations on this task.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression
Mitigating Object Hallucinations via Sentence-Level Early Intervention
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in Conversation
FinAI-BERT: A Transformer-Based Model for Sentence-Level Detection of AI Disclosures in Financial Reports
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
토론
이 논문과 연결된 포럼 글이 아직 없습니다.