Papers Decipherment
“Decipherment” 태그가 달린 논문 46편 · 필터 해제
OracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography
As one of the earliest ancient languages, Oracle Bone Script (OBS) encapsulates the cultural records and intellectual expressions of ancient civilizations. Despite the discovery of approximately 4,500 OBS characters, onl…
DeciphermentLarge Language ModelMultimodal Large Language ModelVisual LocalizationAncient Script Image Recognition and Processing: A Review
Ancient scripts, e.g., Egyptian hieroglyphs, Oracle Bone Inscriptions, and Ancient Greek inscriptions, serve as vital carriers of human civilization, embedding invaluable historical and cultural information. Automating a…
DeciphermentFew-Shot LearningReasoning Over the Glyphs: Evaluation of LLM's Decipherment of Rare Scripts
We explore the capabilities of LVLMs and LLMs in deciphering rare scripts not encoded in Unicode. We introduce a novel approach to construct a multimodal dataset of linguistic puzzles involving such scripts, utilizing a …
DeciphermentDetermination of language families using deep learning
We use a c-GAN (convolutional generative adversarial) neural network to analyze transliterated text fragments of extant, dead comprehensible, and one dead non-deciphered (Cypro-Minoan) language to establish linguistic af…
DeciphermentDeep LearningTranslationOracle Bone Inscriptions Multi-modal Dataset
Oracle bone inscriptions(OBI) is the earliest developed writing system in China, bearing invaluable written exemplifications of early Shang history and paleography. However, the task of deciphering OBI, in the current cl…
DeciphermentDenoisingDecipherment-Aware Multilingual Learning in Jointly Trained Language Models
The principle that governs unsupervised multilingual learning (UCL) in jointly trained language models (mBERT as a popular example) is still being debated. Many find it surprising that one can achieve UCL with multiple m…
DeciphermentDeciphering Oracle Bone Language with Diffusion Models
Originating from China's Shang Dynasty approximately 3,000 years ago, the Oracle Bone Script (OBS) is a cornerstone in the annals of linguistic history, predating many established writing systems. Despite the discovery o…
DeciphermentImage GenerationSegmentation of Maya hieroglyphs through fine-tuned foundation models
The study of Maya hieroglyphic writing unlocks the rich history of cultural and societal knowledge embedded within this ancient civilization's visual narrative. Artificial Intelligence (AI) offers a novel lens through wh…
DeciphermentAn open dataset for oracle bone script recognition and decipherment
Oracle bone script, one of the earliest known forms of ancient Chinese writing, presents invaluable research materials for scholars studying the humanities and geography of the Shang Dynasty, dating back 3,000 years. The…
DeciphermentAn open dataset for the evolution of oracle bone characters: EVOBC
The earliest extant Chinese characters originate from oracle bone inscriptions, which are closely related to other East Asian languages. These inscriptions hold immense value for anthropology and archaeology. However, de…
DeciphermentChatABL: Abductive Learning via Natural Language Interaction with ChatGPT
Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human natural language. However, LLMs current…
DeciphermentLogical ReasoningFrom Inscription to Semi-automatic Annotation of Maya Hieroglyphic Texts
The Maya script is the only readable autochthonous writing system of the Americas and consists of more than 1000 word signs and syllables. It is only partially deciphered and is the subject of the project “Text Database …
DeciphermentTransliterationDorabella Cipher as Musical Inspiration
The Dorabella cipher is an encrypted note of English composer Edward Elgar, which has defied decipherment attempts for more than a century. While most proposed solutions are English texts, we investigate the hypothe- sis…
DeciphermentPositionDeciphering Speech: a Zero-Resource Approach to Cross-Lingual Transfer in ASR
We present a method for cross-lingual training an ASR system using absolutely no transcribed training data from the target language, and with no phonetic knowledge of the language in question. Our approach uses a novel a…
Cross-Lingual ASRCross-Lingual TransferDeciphermentA Text GAN for Language Generation with Non-Autoregressive Generator
Despite the great success of Generative Adversarial Networks (GANs) in generating high-quality images, GANs for text generation still face two major challenges: first, most text GANs are unstable in training mainly due t…
DeciphermentRepresentation LearningSentenceText GenerationCan Sequence-to-Sequence Models Crack Substitution Ciphers?
Decipherment of historical ciphers is a challenging problem. The language of the target plaintext might be unknown, and ciphertext can have a lot of noise. State-of-the-art decipherment methods use beam search and a neur…
DeciphermentLanguage IdentificationLanguage ModelingLanguage ModellingDeciphering Undersegmented Ancient Scripts Using Phonetic Prior
Most undeciphered lost languages exhibit two characteristics that pose significant decipherment challenges: (1) the scripts are not fully segmented into words; (2) the closest known language is not determined. We propose…
DeciphermentPhonetic and Visual Priors for Decipherment of Informal Romanization
Informal romanization is an idiosyncratic process used by humans in informal digital communication to encode non-Latin script languages into Latin character sets found on common keyboards. Character substitution choices …
DeciphermentInductive BiasA Probabilistic Formulation of Unsupervised Text Style Transfer
We present a deep generative model for unsupervised text style transfer that unifies previously proposed non-generative techniques. Our probabilistic approach models non-parallel data from two domains as a partially obse…
DeciphermentLanguage ModellingMachine TranslationStyle Transfer+5Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
In this paper we propose a novel neural approach for automatic decipherment of lost languages. To compensate for the lack of strong supervision signal, our model design is informed by patterns in language change document…
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