https://github.com/ytongxie/pairaug
공식 코드PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding
Introducing Visual Perception Token into Multimodal Large Language Model
Unicorn: Text-Only Data Synthesis for Vision Language Model Training
Soundscape Captioning using Sound Affective Quality Network and Large Language Model
HyPe: Better Pre-trained Language Model Fine-tuning with Hidden Representation Perturbation
Identifying Conspiracy Theories News based on Event Relation Graph
Sentence-level Media Bias Analysis with Event Relation Graph
PromptCL: Improving Event Representation via Prompt Template and Contrastive Learning
Control Industrial Automation System with Large Language Model Agents
Multiscale Positive-Unlabeled Detection of AI-Generated Texts
Rethinking Optimization and Architecture for Tiny Language Models
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Detection of circular permutations by Protein Language Models
Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
AlignScore: Evaluating Factual Consistency with a Unified Alignment Function
G-Refer: Graph Retrieval-Augmented Large Language Model for Explainable Recommendation
Towards Universal Fake Image Detectors that Generalize Across Generative Models
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.