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Paraphrase Identification
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The goal of Paraphrase Identification is to determine whether a pair of sentences have the same meaning.
Source: Adversarial Examples with Difficult Common Words for Paraphrase Identification
Image source: On Paraphrase Identification Corpora
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked Data
Enhancing Plagiarism Detection in Marathi with a Weighted Ensemble of TF-IDF and BERT Embeddings for Low-Resource Language Processing
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Application Specific Compression of Deep Learning Models
Cross-lingual paraphrase identification
Is Modularity Transferable? A Case Study through the Lens of Knowledge Distillation
Memory-efficient Stochastic methods for Memory-based Transformers
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Do Multilingual Language Models Think Better in English?
Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding
Assessing Word Importance Using Models Trained for Semantic Tasks
Cross-functional Analysis of Generalisation in Behavioural Learning
SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases
Co-Driven Recognition of Semantic Consistency via the Fusion of Transformer and HowNet Sememes Knowledge
Paraphrase Identification with Deep Learning: A Review of Datasets and Methods
Improving word mover's distance by leveraging self-attention matrix
Scaling Instruction-Finetuned Language Models
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models
Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders
Improving Large-scale Paraphrase Acquisition and Generation
GAPX: Generalized Autoregressive Paraphrase-Identification X
Paraphrasing, textual entailment, and semantic similarity above word level
Adversarial Self-Attention for Language Understanding
NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures
Match-Prompt: Improving Multi-task Generalization Ability for Neural Text Matching via Prompt Learning
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
PerPaDa: A Persian Paraphrase Dataset based on Implicit Crowdsourcing Data Collection
Explaining Predictive Uncertainty by Looking Back at Model Explanations
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Task-adaptive Pre-training and Self-training are Complementary for Natural Language Understanding
How much pretraining data do language models need to learn syntax?
Contextualized Embeddings based Convolutional Neural Networks for Duplicate Question Identification
Accurate, yet inconsistent? Consistency Analysis on Language Understanding Models
LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching
Modelling Latent Translations for Cross-Lingual Transfer
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