https://github.com/amazon-research/datatuner
공식 코드Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity
Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation
Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
Non-autoregressive Sequence-to-Sequence Vision-Language Models
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation
Large Language Model Critics for Execution-Free Evaluation of Code Changes
Distributionally robust self-supervised learning for tabular data
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
A Cheaper and Better Diffusion Language Model with Soft-Masked Noise
Musketeer: Joint Training for Multi-task Vision Language Model with Task Explanation Prompts
SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
Guiding Attention for Self-Supervised Learning with Transformers
Benchmarking Long-tail Generalization with Likelihood Splits
A Second Wave of UD Hebrew Treebanking and Cross-Domain Parsing
Stochastic positional embeddings improve masked image modeling
On Recovering Higher-order Interactions from Protein Language Models
OffensiveLang: A Community Based Implicit Offensive Language Dataset
ReCAM@IITK at SemEval-2021 Task 4: BERT and ALBERT based Ensemble for Abstract Word Prediction
MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory
AMOM: Adaptive Masking over Masking for Conditional Masked Language Model
Putting words in context: LSTM language models and lexical ambiguity
Bayesian Neural Network Language Modeling for Speech Recognition
Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales
Mobile-VideoGPT: Fast and Accurate Video Understanding Language Model
RouterRetriever: Routing over a Mixture of Expert Embedding Models
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.