https://github.com/uta-sprlab/phishlang
공식 코드PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
Improving Visual Grounding by Encouraging Consistent Gradient-based Explanations
Event-based clinical findings extraction from radiology reports with pre-trained language model
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages
Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval
A Batch Normalized Inference Network Keeps the KL Vanishing Away
DagoBERT: Generating Derivational Morphology with a Pretrained Language Model
A Realistic Threat Model for Large Language Model Jailbreaks
Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement
Discovering Preference Optimization Algorithms with and for Large Language Models
L2MAC: Large Language Model Automatic Computer for Extensive Code Generation
FaaF: Facts as a Function for the evaluation of generated text
Breaking Time Invariance: Assorted-Time Normalization for RNNs
IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration
Reasoning-Grounded Natural Language Explanations for Language Models
LLMZip: Lossless Text Compression using Large Language Models
MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems
Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding
Hessian of Perplexity for Large Language Models by PyTorch autograd (Open Source)
Thanos: A Block-wise Pruning Algorithm for Efficient Large Language Model Compression
Lil-Bevo: Explorations of Strategies for Training Language Models in More Humanlike Ways
Counterfactually Probing Language Identity in Multilingual Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.