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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/DeepSoftwareAnalytics/CoSQA_Plus
공식 코드CoSQA+: Pioneering the Multi-Choice Code Search Benchmark with Test-Driven Agents
https://github.com/DeutscheKI/tevr-asr-tool
공식 코드TEVR: Improving Speech Recognition by Token Entropy Variance Reduction
https://github.com/DevSinghSachan/art
공식 코드Questions Are All You Need to Train a Dense Passage Retriever
https://github.com/DevSinghSachan/unsupervised-passage-reranking
공식 코드Improving Passage Retrieval with Zero-Shot Question Generation
https://github.com/Dongzhikang/MuseChat-dataset
공식 코드MuseChat: A Conversational Music Recommendation System for Videos
https://github.com/Doraemonzzz/tnn-pytorch
공식 코드https://github.com/DreamH1gh/TACL2024
공식 코드Retrieval-style In-Context Learning for Few-shot Hierarchical Text Classification
https://github.com/EagleW/Stage-wise-Fine-tuning
공식 코드https://github.com/EarlFan/ChatCFD
공식 코드ChatCFD: an End-to-End CFD Agent with Domain-specific Structured Thinking
https://github.com/EdinburghClinicalNLP/semeval_nli4ct
공식 코드Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4
https://github.com/Edward-Sun/SLM
공식 코드Unsupervised Neural Word Segmentation for Chinese via Segmental Language Modeling
https://github.com/EleutherAI/The-Pile
공식 코드The Pile: An 800GB Dataset of Diverse Text for Language Modeling
https://github.com/EleutherAI/math-lm
공식 코드https://github.com/EleutherAI/rnngineering
공식 코드https://github.com/EmergentSystemLabStudent/Prosodic-DAA
공식 코드Double Articulation Analyzer with Prosody for Unsupervised Word and Phoneme Discovery
https://github.com/EminLU/UniDetox
공식 코드UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
https://github.com/EmpathYang/ADEPT
공식 코드https://github.com/Ereboas/TacoLM
공식 코드https://github.com/Eric-Wallace/universal-triggers
공식 코드Universal Adversarial Triggers for Attacking and Analyzing NLP
https://github.com/ErikEkstedt/TurnGPT
공식 코드TurnGPT: a Transformer-based Language Model for Predicting Turn-taking in Spoken Dialog
https://github.com/EruM16/Attention-Seeker
공식 코드Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction
https://github.com/ErxinYu/CoSafe-Dataset
공식 코드CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreference
https://github.com/EthanLifeGreat/SuDoSys
공식 코드Structured Dialogue System for Mental Health: An LLM Chatbot Leveraging the PM+ Guidelines
https://github.com/EvLab-MIT/LexiContrastiveGrd
공식 코드Visual Grounding Helps Learn Word Meanings in Low-Data Regimes
https://github.com/EvalCrafter/EvalCrafter
공식 코드EvalCrafter: Benchmarking and Evaluating Large Video Generation Models
https://github.com/EvanZhuang/vector-icl
공식 코드Vector-ICL: In-context Learning with Continuous Vector Representations
https://github.com/ExplainableML/DeViL
공식 코드https://github.com/Exploration-Lab/FineGrained-Emotion-Prediciton-Using-Definitions
공식 코드Fine-Grained Emotion Prediction by Modeling Emotion Definitions
https://github.com/Extreme-classification/DECAF
공식 코드https://github.com/FAIRNS/Number_and_syntax_units_in_LSTM_LMs
공식 코드The emergence of number and syntax units in LSTM language models
https://github.com/FKIRSTE/emnlp2024-personalized-meeting-sum
공식 코드https://github.com/FaisalQarah/EgyBERT
공식 코드EgyBERT: A Large Language Model Pretrained on Egyptian Dialect Corpora
https://github.com/FangShancheng/ABINet
공식 코드https://github.com/Fangkang515/CE3D
공식 코드https://github.com/FarnoushRJ/MambaLRP
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.