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Sentence Pair Modeling

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Comparing two sentences and their relationship based on their internal representation.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/shanzhenren/PLE

공식 코드

Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

https://github.com/sharif-slpl/se-2024-task-06-shroom

공식 코드

SLPL SHROOM at SemEval2024 Task 06: A comprehensive study on models ability to detect hallucination

https://github.com/shenzheng2000/tpsence

공식 코드

TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain

https://github.com/showlab/diffsim

공식 코드

DiffSim: Taming Diffusion Models for Evaluating Visual Similarity

https://github.com/shubha07m/Energy-optimized-semantic-loss

공식 코드

Transformers for Green Semantic Communication: Less Energy, More Semantics

https://github.com/shumingma/SRB

공식 코드

A Semantic Relevance Based Neural Network for Text Summarization and Text Simplification

https://github.com/sicara/semantic-task-sampling

공식 코드

Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task Sampling

https://github.com/sinovation/ZEN

공식 코드

ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations

https://github.com/smartandcleverrobot/icra-cirn

공식 코드

Zero-Shot Object Goal Visual Navigation With Class-Independent Relationship Network

https://github.com/sohomghosh/FinSim_Financial_Hypernym_detection

공식 코드

Term Expansion and FinBERT fine-tuning for Hypernym and Synonym Ranking of Financial Terms

https://github.com/solar-group/agileeffortestimation

공식 코드

Agile Effort Estimation: Have We Solved the Problem Yet? Insights From A Replication Study

https://github.com/sssadrizadeh/transfool

공식 코드

TransFool: An Adversarial Attack against Neural Machine Translation Models

https://github.com/stanfordnlp/treelstm

공식 코드

Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

https://github.com/steffeneger/global-explainability-metrics

공식 코드

Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors

https://github.com/steventan0110/NMTModelAttack

공식 코드

Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation

https://github.com/sunisfighting/signa

공식 코드

Single-View Graph Contrastive Learning with Soft Neighborhood Awareness

https://github.com/swaroop-nath/rl-qfs

공식 코드

Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning

https://github.com/sydney-machine-learning/sentimentanalysis_bhagavadgita

공식 코드

Semantic and sentiment analysis of selected Bhagavad Gita translations using BERT-based language framework

https://github.com/tawald/semantic_rsm

공식 코드

Decoupling Semantic Similarity from Spatial Alignment for Neural Networks

https://github.com/tbmihailov/semeval2016-task3-CQA

공식 코드

SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings

https://github.com/tca19/near-lossless-binarization

공식 코드

Near-lossless Binarization of Word Embeddings

https://github.com/thompsonb/prism

공식 코드

Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity

https://github.com/thu-coai/HINT

공식 코드

Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence

https://github.com/thuiar/textoir

공식 코드

A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery

https://github.com/tianyu139/meaning-as-trajectories

공식 코드

Meaning Representations from Trajectories in Autoregressive Models

https://github.com/timpal0l/sts-benchmark-swedish

공식 코드

Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity

https://github.com/timrudner/function-space-empirical-bayes

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Function-Space Regularization in Neural Networks: A Probabilistic Perspective

https://github.com/tjzvbokbnft/ELITE-Embedding-Less-retrieval-with-Iterative-Text-Exploration

공식 코드

ELITE: Embedding-Less retrieval with Iterative Text Exploration

https://github.com/ttuhamg/driveditfit

공식 코드

DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous Driving

https://github.com/tumeteor/ttp-mapping

공식 코드

Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition

https://github.com/ubc-nlp/turjuman

공식 코드

TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation

https://github.com/uclanlp/ParaBART

공식 코드

Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models

https://github.com/uclanlp/paraamr

공식 코드

ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation

https://github.com/uhh-lt/path2vec

공식 코드

Making Fast Graph-based Algorithms with Graph Metric Embeddings

https://github.com/umdatasciencelab/uncertainty-quantification-for-llms

공식 코드

Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language Models

https://github.com/usc-tamagotchi/dh-mlm

공식 코드

The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining

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