https://github.com/cancanxxx/round_trip_translation_defence
공식 코드Round Trip Translation Defence against Large Language Model Jailbreaking Attacks
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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Round Trip Translation Defence against Large Language Model Jailbreaking Attacks
Online Detecting LLM-Generated Texts via Sequential Hypothesis Testing by Betting
Conditionally Learn to Pay Attention for Sequential Visual Task
Pretrained Language Models for Dialogue Generation with Multiple Input Sources
AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection
TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification
XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond
An Invariant Learning Characterization of Controlled Text Generation
RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation
Recycled Attention: Efficient inference for long-context language models
Text Smoothing: Enhance Various Data Augmentation Methods on Text Classification Tasks
LyapLock: Bounded Knowledge Preservation in Sequential Large Language Model Editing
InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings
InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings
DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization
What Do Llamas Really Think? Revealing Preference Biases in Language Model Representations
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale
Why do language models perform worse for morphologically complex languages?
Identifying and Extracting Rare Disease Phenotypes with Large Language Models
INO at Factify 2: Structure Coherence based Multi-Modal Fact Verification
Toward a Deeper Understanding: RetNet Viewed through Convolution
JavaBERT: Training a transformer-based model for the Java programming language
Language Model Prior for Low-Resource Neural Machine Translation
Exploring Unsupervised Pretraining Objectives for Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.