Language Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 55
- 보존된 평가 기록
- 466
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/wilcoxeg/targeted-assessment-imaze
공식 코드A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humans
https://github.com/wilkox/gptscreenr
공식 코드Automated title and abstract screening for scoping reviews using the GPT-4 Large Language Model
https://github.com/willemeng/VLScene
공식 코드VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion
https://github.com/willemsenbram/mention-detection-vgd
공식 코드Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
https://github.com/willemsenbram/reference-resolution-via-text-generation
공식 코드Resolving References in Visually-Grounded Dialogue via Text Generation
https://github.com/willhawkins3/finetuningtoxicity
공식 코드https://github.com/williamliujl/Qilin-Med
공식 코드Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
https://github.com/williamliujl/qilin-med-vl
공식 코드Qilin-Med-VL: Towards Chinese Large Vision-Language Model for General Healthcare
https://github.com/williamzr/recipe2plan
공식 코드https://github.com/willxxy/ecg-byte
공식 코드ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling
https://github.com/willxxy/text-egm
공식 코드Interpretation of Intracardiac Electrograms Through Textual Representations
https://github.com/windvchen/diff-harmonization
공식 코드https://github.com/wisdomshell/freeeval
공식 코드FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
https://github.com/wishever/mmidr
공식 코드https://github.com/wispcarey/autokg
공식 코드AutoKG: Efficient Automated Knowledge Graph Generation for Language Models
https://github.com/wisper12933/ga-rollback
공식 코드Generator-Assistant Stepwise Rollback Framework for Large Language Model Agent
https://github.com/wivizhang/earthgpt
공식 코드https://github.com/wivizhang/earthmarker
공식 코드EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote Sensing
https://github.com/wiwu2390/futuregpt2-public
공식 코드https://github.com/wj210/Self-Training-LLM
공식 코드Self-training Large Language Models through Knowledge Detection
https://github.com/wjh892521292/lkm-unet
공식 코드LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation
https://github.com/wjh892521292/lma-unet
공식 코드LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation
https://github.com/wjj0122/arallm
공식 코드https://github.com/wjn1996/kp-plm
공식 코드Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding
https://github.com/wjurayj/garden-path-gpt2
공식 코드https://github.com/wjxts/regularizedbn
공식 코드Understanding the Failure of Batch Normalization for Transformers in NLP
https://github.com/wkfdb/marvelovd
공식 코드https://github.com/wlik/glrec
공식 코드Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations
https://github.com/wlin12/JNN
공식 코드Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation
https://github.com/wojciechowskiofficial/flex
공식 코드Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach
https://github.com/wojzaremba/lstm
공식 코드https://github.com/woojeongjin/fewvlm
공식 코드https://github.com/woooodyy/agentgym
공식 코드AgentGym: Evolving Large Language Model-based Agents across Diverse Environments
https://github.com/woooodyy/llm-agent-paper-list
공식 코드The Rise and Potential of Large Language Model Based Agents: A Survey
https://github.com/wordsgpt/llm_vocabulary_evaluation
공식 코드Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.