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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/worta/trojansteno
공식 코드TrojanStego: Your Language Model Can Secretly Be A Steganographic Privacy Leaking Agent
https://github.com/wqxleo/kcf-plm
공식 코드https://github.com/wtma/CharBERT
공식 코드https://github.com/wuhy68/chatedav1
공식 코드ChatEDA: A Large Language Model Powered Autonomous Agent for EDA
https://github.com/wujiangxu/slmrec
공식 코드SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
https://github.com/wujiong-hub/cdpdnet
공식 코드CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation
https://github.com/wujwyi/cmc
공식 코드Cross-model Control: Improving Multiple Large Language Models in One-time Training
https://github.com/wuklab/infercept
공식 코드InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
https://github.com/wuning0929/ccp_ijcai22
공식 코드Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval
https://github.com/wusiwei0410/mmra
공식 코드https://github.com/wutaiqiang/ger-wsdm2023
공식 코드https://github.com/wutong8023/versicode
공식 코드https://github.com/wuuu110/Hercules
공식 코드https://github.com/wuxingyu-ai/as-llm
공식 코드Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
https://github.com/wuxingyu-ai/llm4ec
공식 코드Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap
https://github.com/wuyike2000/retrieve-rewrite-answer
공식 코드Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
https://github.com/wwbrannon/congrat
공식 코드ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings
https://github.com/wwwadx/FinVis-GPT
공식 코드FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis
https://github.com/wwzll123/esm-nbr
공식 코드https://github.com/wxj77/meetingsummarization
공식 코드Meeting Summarization with Pre-training and Clustering Methods
https://github.com/wxy3596/asma-tune
공식 코드ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning
https://github.com/wyddmw/WiseAD
공식 코드WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model
https://github.com/wyharturia/llm_enhanced_ml
공식 코드Large Language Model Enhanced Machine Learning Estimators for Classification
https://github.com/wyripple/rp_kw_errors
공식 코드Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing
https://github.com/wyshi/lm_privacy
공식 코드https://github.com/wyu-du/self-training-dialogue-generation
공식 코드Self-training with Two-phase Self-augmentation for Few-shot Dialogue Generation
https://github.com/wyu97/GenRead
공식 코드Generate rather than Retrieve: Large Language Models are Strong Context Generators
https://github.com/wyxstriker/MakeSomeNoiseInference
공식 코드Make Some Noise: Unlocking Language Model Parallel Inference Capability through Noisy Training
https://github.com/wzh9969/hpt
공식 코드HPT: Hierarchy-aware Prompt Tuning for Hierarchical Text Classification
https://github.com/wzy232303/fpt
공식 코드FPT: Feature Prompt Tuning for Few-shot Readability Assessment
https://github.com/x-lance/mobile-env
공식 코드Mobile-Env: Building Qualified Evaluation Benchmarks for LLM-GUI Interaction
https://github.com/x-lance/tie
공식 코드TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages
https://github.com/x-plug/mplug-docowl
공식 코드mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
https://github.com/x-plug/mplug-halowl
공식 코드Hallucination Augmented Contrastive Learning for Multimodal Large Language Model
https://github.com/x-plug/mplug-owl
공식 코드mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.