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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/mct10/repcodec
공식 코드RepCodec: A Speech Representation Codec for Speech Tokenization
https://github.com/mdda/worldtree_corpus
공식 코드Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
https://github.com/mdoumbouya/codeocr
공식 코드https://github.com/mdrpanwar/icl-bayesian-prism
공식 코드https://github.com/measure-infinity/mulan-code
공식 코드MuLan: Multimodal-LLM Agent for Progressive and Interactive Multi-Object Diffusion
https://github.com/med-air/picg2scoring
공식 코드https://github.com/medbar/kaldi/tree/ltlm/egs/librispeech/s5/fairseq_ltlm
공식 코드LT-LM: a novel non-autoregressive language model for single-shot lattice rescoring
https://github.com/meddjilani/fashionrecommender
공식 코드Trend-Aware Fashion Recommendation with Visual Segmentation and Semantic Similarity
https://github.com/medfound/medfound
공식 코드https://github.com/mediabrain-sjtu/ming
공식 코드https://github.com/medicinetoken/medical-graph-rag
공식 코드https://github.com/medtray/SeLaB
공식 코드Semantic Labeling Using a Deep Contextualized Language Model
https://github.com/meettyj/gnp
공식 코드https://github.com/megagonlabs/emu
공식 코드Emu: Enhancing Multilingual Sentence Embeddings with Semantic Specialization
https://github.com/megagonlabs/rjdb
공식 코드Distilling Large Language Models using Skill-Occupation Graph Context for HR-Related Tasks
https://github.com/megagonlabs/zett
공식 코드https://github.com/megvii-research/caspl
공식 코드Cascade Prompt Learning for Vision-Language Model Adaptation
https://github.com/mehdimojarradi/Ensemble-SuperICL
공식 코드Improving In-Context Learning with Small Language Model Ensembles
https://github.com/mehrdadghassabi/gaokerena
공식 코드Leveraging Online Data to Enhance Medical Knowledge in a Small Persian Language Model
https://github.com/meinwerk/WordPrediction
공식 코드https://github.com/meisin/commodity-news-event-extraction
공식 코드https://github.com/meituan-automl/mobilevlm
공식 코드MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices
https://github.com/melih-unsal/demogpt
공식 코드https://github.com/melzohbi/poem-rhythm
공식 코드Let the Poem Hit the Rhythm: Using a Byte-Based Transformer for Beat-Aligned Poetry Generation
https://github.com/memberre/asyncdriver
공식 코드Asynchronous Large Language Model Enhanced Planner for Autonomous Driving
https://github.com/mendelxu/san
공식 코드Side Adapter Network for Open-Vocabulary Semantic Segmentation
https://github.com/mendelxu/zsseg.baseline
공식 코드A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model
https://github.com/mengchuang123/vasparse-github
공식 코드https://github.com/mengdanzhu/cross-modal-rag
공식 코드Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image Generation
https://github.com/mengqidyangge/hierkd
공식 코드Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation
https://github.com/mengxiayu/llmsuperweight
공식 코드https://github.com/merlresearch/SMART
공식 코드https://github.com/meryemmhamdi1/meta_cross_nlu_qa
공식 코드https://github.com/meshidenn/cai
공식 코드Unsupervised Domain Adaptation for Sparse Retrieval by Filling Vocabulary and Word Frequency Gaps
https://github.com/meshinfra/waferllm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.