Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mayo-radiology-informatics-lab/conflare
공식 코드https://github.com/mayubo2333/llm-ie
공식 코드https://github.com/mazumder-lab/comet
공식 코드COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search
https://github.com/mbilalzafar/fair-classification
공식 코드https://github.com/mbzuai-nlp/arabicmmlu
공식 코드ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic
https://github.com/mbzuai-nlp/fire
공식 코드FIRE: Fact-checking with Iterative Retrieval and Verification
https://github.com/mbzuai-oryx/geochat
공식 코드GeoChat: Grounded Large Vision-Language Model for Remote Sensing
https://github.com/mbzuai-oryx/palo
공식 코드https://github.com/mbzuai-oryx/xraygpt
공식 코드XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models
https://github.com/mcgill-nlp/bias-bench
공식 코드An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models
https://github.com/mcgill-nlp/debias-eval
공식 코드An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models
https://github.com/mcgill-nlp/logicalknowedit
공식 코드Evaluating Dependencies in Fact Editing for Language Models: Specificity and Implication Awareness
https://github.com/mcgill-nlp/retriever-lm-reasoning
공식 코드https://github.com/mcgill-nlp/syntactic-substitutability
공식 코드Syntactic Substitutability as Unsupervised Dependency Syntax
https://github.com/mcleish7/gemstone-scaling-laws
공식 코드https://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/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/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/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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.