https://github.com/peluz/persona-behavior
공식 코드Helpful assistant or fruitful facilitator? Investigating how personas affect language model behavior
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Helpful assistant or fruitful facilitator? Investigating how personas affect language model behavior
Plug & Play Directed Evolution of Proteins with Gradient-based Discrete MCMC
WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Self-supervised vision-language pretraining for Medical visual question answering
MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models
LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model
CELA: Cost-Efficient Language Model Alignment for CTR Prediction
PromptShots at the FinNLP-2022 ERAI Tasks: Pairwise Comparison and Unsupervised Ranking
Evaluating context-invariance in unsupervised speech representations
FGeo-DRL: Deductive Reasoning for Geometric Problems through Deep Reinforcement Learning
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation
Learning Multiplex Representations on Text-Attributed Graphs with One Language Model Encoder
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations
Document Informed Neural Autoregressive Topic Models with Distributional Prior
L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks
Bridge the Gap Between CV and NLP! A Gradient-based Textual Adversarial Attack Framework
MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering
BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine
SGC-Net: Stratified Granular Comparison Network for Open-Vocabulary HOI Detection
Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance
Knowledge-Augmented Language Models for Cause-Effect Relation Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.