https://github.com/prabaey/synsum
공식 코드SynSUM -- Synthetic Benchmark with Structured and Unstructured Medical Records
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
SynSUM -- Synthetic Benchmark with Structured and Unstructured Medical Records
Resource-Aware Arabic LLM Creation: Model Adaptation, Integration, and Multi-Domain Testing
Alignment Analysis of Sequential Segmentation of Lexicons to Improve Automatic Cognate Detection
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in Conversation
Keep CALM and Explore: Language Models for Action Generation in Text-based Games
Long-Context Language Modeling with Parallel Context Encoding
Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
SemSup: Semantic Supervision for Simple and Scalable Zero-shot Generalization
EnIGMA: Enhanced Interactive Generative Model Agent for CTF Challenges
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Metadata Conditioning Accelerates Language Model Pre-training
What Makes a Reward Model a Good Teacher? An Optimization Perspective
ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Experts
What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study
LML-DAP: Language Model Learning a Dataset for Data-Augmented Prediction
Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.