Language Modelling
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A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/UNHSAILLab/SentimentalLIAR
공식 코드Sentimental LIAR: Extended Corpus and Deep Learning Models for Fake Claim Classification
https://github.com/UTibetNLP/TSTricker
공식 코드Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
https://github.com/Unbabel/COMET
공식 코드https://github.com/UtsaChattopadhyay/MSAI/blob/main/SourceCode%20for%20low%20Resource%20MT.zip
공식 코드https://github.com/VARGPT-family/VARGPT
공식 코드https://github.com/VDIGPKU/IterNet
공식 코드IterVM: Iterative Vision Modeling Module for Scene Text Recognition
https://github.com/VDIGPKU/OpenAD
공식 코드OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection
https://github.com/VITA-Group/BERT-Tickets
공식 코드https://github.com/VITA-MLLM/VITA
공식 코드https://github.com/Valdecy/pyDecision
공식 코드https://github.com/Varal7/blank_language_model
공식 코드https://github.com/VectorInstitute/biaskg
공식 코드BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models
https://github.com/VickiCui/Loire
공식 코드Beyond Language: Learning Commonsense from Images for Reasoning
https://github.com/VinAIResearch/BERTweet
공식 코드https://github.com/VinAIResearch/PhoBERT
공식 코드https://github.com/VinAIResearch/PhoNER_COVID19
공식 코드https://github.com/VinAIResearch/PhoNLP
공식 코드https://github.com/VinAIResearch/ViText2SQL
공식 코드A Pilot Study of Text-to-SQL Semantic Parsing for Vietnamese
https://github.com/VinceFior/major-system
공식 코드https://github.com/VirajBagal/MMBERT
공식 코드MMBERT: Multimodal BERT Pretraining for Improved Medical VQA
https://github.com/Vision-CAIR/MiniGPT4-video
공식 코드https://github.com/Vision-CAIR/VisualGPT
공식 코드VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning
https://github.com/VodLM/vod
공식 코드https://github.com/VoyagerXvoyagerx/InstructSAM
공식 코드InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition
https://github.com/WANGBohaO-jpg/MSL
공식 코드MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender
https://github.com/WENGSYX/Self-Verification
공식 코드Large Language Models are Better Reasoners with Self-Verification
https://github.com/WPENGxs/X-WebAgentBench
공식 코드X-WebAgentBench: A Multilingual Interactive Web Benchmark for Evaluating Global Agentic System
https://github.com/WSP-LAB/Montage
공식 코드Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer
https://github.com/Wang-Haining/noveval
공식 코드A Content-Based Novelty Measure for Scholarly Publications: A Proof of Concept
https://github.com/Wang-Haining/scholarly_abstract_simplification
공식 코드Simplifying Scholarly Abstracts for Accessible Digital Libraries
https://github.com/WangCan1178/Plug-and-Play-Estimation
공식 코드Plug-and-Play Performance Estimation for LLM Services without Relying on Labeled Data
https://github.com/WangHanLinHenry/STeCa
공식 코드STeCa: Step-level Trajectory Calibration for LLM Agent Learning
https://github.com/WangRongsheng/IvyGPT
공식 코드IvyGPT: InteractiVe Chinese pathwaY language model in medical domain
https://github.com/WangYuxuan93/CLBT
공식 코드Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing
https://github.com/WanzhengZhu/Euphemism
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.