Language Modeling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aashiqmuhamed/grass
공식 코드Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
https://github.com/aatlantise/punc-rest-improves
공식 코드Punctuation Restoration Improves Structure Understanding Without Supervision
https://github.com/abacinlp/investlm
공식 코드InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning
https://github.com/abc03570128/jailbreaking-attack-against-multimodal-large-language-model
공식 코드https://github.com/abderrahmanskiredj/DarijaBanking
공식 코드https://github.com/abdoelsayed2016/grg
공식 코드Generator-Retriever-Generator Approach for Open-Domain Question Answering
https://github.com/abecode/emo20q
공식 코드BERT-Assisted Semantic Annotation Correction for Emotion-Related Questions
https://github.com/abel2code/the_butterfly_effect_of_prompts
공식 코드https://github.com/abhinand5/tamil-llama
공식 코드https://github.com/abhishekpanigrahi1996/transformer_in_transformer
공식 코드https://github.com/abman23/on-device-ai-comm
공식 코드Integrating Pre-Trained Language Model with Physical Layer Communications
https://github.com/abman23/on-device-llm-wifi-roaming
공식 코드https://github.com/aboveparadise/llmcbench
공식 코드LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
https://github.com/ace117mc/transformer-models-covid
공식 코드https://github.com/acfr/cassdetect
공식 코드https://github.com/achandlr/DEEP
공식 코드https://github.com/acharkq/molca
공식 코드MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter
https://github.com/acharkq/next-mol
공식 코드NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
https://github.com/acolas1/GAP_COLING2022
공식 코드GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation
https://github.com/adamits/morphological-inflection-noise
공식 코드https://github.com/adamkarvonen/SAE_BoardGameEval
공식 코드Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
https://github.com/adap/flower
공식 코드https://github.com/adapter-hub/xgqa
공식 코드https://github.com/adbrei/renargen
공식 코드Returning to the Start: Generating Narratives with Related Endpoints
https://github.com/adeeph/memeclassification
공식 코드https://github.com/adeline-cs/GTR
공식 코드Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition
https://github.com/adresgezgini/NLP4AT
공식 코드Auto-tagging of Short Conversational Sentences using Natural Language Processing Methods
https://github.com/adrianbzg/hyperbert
공식 코드https://github.com/adrianbzg/sfavel
공식 코드Unsupervised Pretraining for Fact Verification by Language Model Distillation
https://github.com/adrianbzg/tinyroberta-distillation-qa-es
공식 코드Language Model Knowledge Distillation for Efficient Question Answering in Spanish
https://github.com/ads-ai/k12-bert-aied-2022
공식 코드https://github.com/adxcreative/LEARN
공식 코드https://github.com/aetting/lm-diagnostics
공식 코드What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models
https://github.com/aeye-lab/emnlp-syntheticscanpaths-nlu-pretrainedlm
공식 코드Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding
https://github.com/ag1988/gmat
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.