https://github.com/timothybrooks/instruct-pix2pix
공식 코드InstructPix2Pix: Learning to Follow Image Editing Instructions
Papers with Code 아카이브
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/timpal0l/ScandiSent
공식 코드Should we Stop Training More Monolingual Models, and Simply Use Machine Translation Instead?
https://github.com/timpal0l/sts-benchmark-swedish
공식 코드Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
https://github.com/timqqt/fair_text_based_image_retrieval
공식 코드https://github.com/timrudner/function-space-empirical-bayes
공식 코드Function-Space Regularization in Neural Networks: A Probabilistic Perspective
https://github.com/tingchenfu/poisonbench
공식 코드PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
https://github.com/tinghanf/regluarlrnn
공식 코드Advancing Regular Language Reasoning in Linear Recurrent Neural Networks
https://github.com/tingjshen/urllm
공식 코드https://github.com/tingyu215/vacnic
공식 코드https://github.com/tipt0p/SparseBayesianRNN
공식 코드https://github.com/titech-nlp/repetition-generation
공식 코드https://github.com/tizfa/tweepfake_deepfake_text_detection
공식 코드https://github.com/tjtp/d2controller
공식 코드https://github.com/tjtsai/PianoStyleEmbedding
공식 코드Composer Style Classification of Piano Sheet Music Images Using Language Model Pretraining
https://github.com/tjunlp-lab/awesome-llm-safety-papers
공식 코드https://github.com/tjunlp-lab/cmoraleval
공식 코드CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models
https://github.com/tjunlp-lab/fuxitranyu
공식 코드FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data
https://github.com/tjvsonsbeek/open-ended-medical-vqa
공식 코드Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models
https://github.com/tjzvbokbnft/ELITE-Embedding-Less-retrieval-with-Iterative-Text-Exploration
공식 코드ELITE: Embedding-Less retrieval with Iterative Text Exploration
https://github.com/tk-rusch/lem
공식 코드https://github.com/tkenneweg/rag_dataset_gen
공식 코드https://github.com/tml-epfl/learning-parametric-distributions-from-samples-and-preferences
공식 코드Learning Parametric Distributions from Samples and Preferences
https://github.com/tml2002/rolecraft
공식 코드RoleCraft-GLM: Advancing Personalized Role-Playing in Large Language Models
https://github.com/tmlr-group/deepinception
공식 코드DeepInception: Hypnotize Large Language Model to Be Jailbreaker
https://github.com/tmlr-group/wca
공식 코드Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
https://github.com/tmtuan1307/nayer
공식 코드NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation
https://github.com/tntek/source-free-domain-adaptation
공식 코드https://github.com/tobiaskatsch/GateLoop
공식 코드GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling
https://github.com/toddnief/rate
공식 코드RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
https://github.com/togethercomputer/dragonfly
공식 코드Dragonfly: Multi-Resolution Zoom-In Encoding Enhances Vision-Language Models
https://github.com/toizzy/bread
공식 코드https://github.com/toizzy/tilt-transfer
공식 코드Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models
https://github.com/tolusophy/Edge-of-Tomorrow
공식 코드On the Reliability of Large Language Models to Misinformed and Demographically-Informed Prompts
https://github.com/tom-pelsmaeker/deep-generative-lm
공식 코드https://github.com/tom192180/Generate_then_Refine
공식 코드Generate then Refine: Data Augmentation for Zero-shot Intent Detection
https://github.com/tomchen-ctj/OST
공식 코드OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.