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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/john-hewitt/implicit-ins
공식 코드https://github.com/john-hewitt/model-editing-canonical-examples
공식 코드https://github.com/john-hewitt/truncation-sampling
공식 코드https://github.com/john1226966735/adaptive-solver
공식 코드Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning
https://github.com/johnheo/adadim-llm
공식 코드https://github.com/johnnay/llm-lobbyist
공식 코드https://github.com/johnnychanv/diffusioncls
공식 코드https://github.com/johnnyzn/MalRNN
공식 코드https://github.com/jojacola/fuel
공식 코드Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit View
https://github.com/jojotenya/LAMOL
공식 코드https://github.com/jonasgeiping/cramming
공식 코드Cramming: Training a Language Model on a Single GPU in One Day
https://github.com/jonathanzha47/smartfinrag
공식 코드SMARTFinRAG: Interactive Modularized Financial RAG Benchmark
https://github.com/jonhue/activeft
공식 코드Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
https://github.com/joongbo/tta
공식 코드Fast and Accurate Deep Bidirectional Language Representations for Unsupervised Learning
https://github.com/joonspk-research/generative_agents
공식 코드https://github.com/jordiclive/ControlPrefixes
공식 코드https://github.com/jorge-martinez-gil/sesige
공식 코드Automatic Design of Semantic Similarity Ensembles Using Grammatical Evolution
https://github.com/jorge-martinez-gil/uwsd
공식 코드Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation
https://github.com/josecannete/spanish-corpora
공식 코드https://github.com/josephjeesungsuh/subpop
공식 코드Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions
https://github.com/joshengels/multidimensionalfeatures
공식 코드https://github.com/joshua-ren/iicl
공식 코드Bias Amplification in Language Model Evolution: An Iterated Learning Perspective
https://github.com/joshua-zingale/plug-and-play-rst-ctg
공식 코드Language Model Sentence Completion with a Parser-Driven Rhetorical Control Method
https://github.com/joshuachou2018/autoba
공식 코드https://github.com/josiahwang/phraseloceval
공식 코드https://github.com/josipjukic/adapter-al
공식 코드Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings
https://github.com/joydajunspacecraft/assertion_llm
공식 코드Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
https://github.com/joyheyueya/declarative-math-word-problem
공식 코드Solving Math Word Problems by Combining Language Models With Symbolic Solvers
https://github.com/joylimjy/leceval
공식 코드LecEval: An Automated Metric for Multimodal Knowledge Acquisition in Multimedia Learning
https://github.com/jp2425/scope2
공식 코드Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability Detection
https://github.com/jpickard1/brad
공식 코드https://github.com/jprivera44/EscalAItion
공식 코드Escalation Risks from Language Models in Military and Diplomatic Decision-Making
https://github.com/jrc1995/investigatingrecurrenttransformers
공식 코드https://github.com/jsalfity/task_decomposition
공식 코드https://github.com/jshang123/G-Bert
공식 코드Pre-training of Graph Augmented Transformers for Medication Recommendation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.