Universal Language Modelling agent
원문 초록
Large Language Models are designed to understand complex Human Language. Yet, Understanding of animal language has long intrigued researchers striving to bridge the communication gap between humans and other species. This research paper introduces a novel approach that draws inspiration from the linguistic concepts found in the Quran, a revealed Holy Arabic scripture dating back 1400 years. By exploring the linguistic structure of the Quran, specifically the components of ism, fil, and harf, we aim to unlock the underlying intentions and meanings embedded within animal conversations using audio data. To unravel the intricate complexities of animal language, we employ word embedding techniques to analyze each distinct frequency component. This methodology enables the identification of potential correlations and the extraction of meaningful insights from the data. Furthermore, we leverage a bioacoustics model to generate audio, which serves as a valuable resource for training natural language processing (NLP) techniques. This Paper aims to find the intention* behind animal language rather than having each word translation.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Specification-based Security Evaluation of Real-World Agents Tool-Calling under Long-Horizon Context Tasks
Making Language Model a Hierarchical Classifier and Generator
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
Describe Anything Model for Visual Question Answering on Text-rich Images
Assay2Mol: large language model-based drug design using BioAssay context
Kodezi Chronos: A Debugging-First Language Model for Repository-Scale, Memory-Driven Code Understanding
토론
이 논문과 연결된 포럼 글이 아직 없습니다.