https://github.com/hsaest/quert
공식 코드QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search
Automated Validation of Textual Constraints Against AutomationML via LLMs and SHACL
Visual-Language Prompt Tuning with Knowledge-guided Context Optimization
TCP:Textual-based Class-aware Prompt tuning for Visual-Language Model
STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
Token-wise Influential Training Data Retrieval for Large Language Models
Multiscale Positive-Unlabeled Detection of AI-Generated Texts
Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order
TinyBERT: Distilling BERT for Natural Language Understanding
Enhancing Transformers with Gradient Boosted Decision Trees for NLI Fine-Tuning
MaskPure: Improving Defense Against Text Adversaries with Stochastic Purification
SELFormer: Molecular Representation Learning via SELFIES Language Models
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
From Interests to Insights: An LLM Approach to Course Recommendations Using Natural Language Queries
Personalized Language Modeling from Personalized Human Feedback
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.