Papers with Code 아카이브
Semantic Textual Similarity
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 13
- 보존된 평가 기록
- 280
Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.
Image source: Learning Semantic Textual Similarity from Conversations
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nmrksic/lear
공식 코드https://github.com/nokia/code-compass
공식 코드https://github.com/nuochenpku/sscl
공식 코드Alleviating Over-smoothing for Unsupervised Sentence Representation
https://github.com/nusnlp/Self-J
공식 코드Self-Judge: Selective Instruction Following with Alignment Self-Evaluation
https://github.com/nweir127/COD3S
공식 코드https://github.com/o-vigia/gma3d
공식 코드GMA3D: Local-Global Attention Learning to Estimate Occluded Motions of Scene Flow
https://github.com/oaraque/moral-foundations
공식 코드MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction
https://github.com/odedh/textual-pca
공식 코드https://github.com/omossad/fat-albert
공식 코드FAT ALBERT: Finding Answers in Large Texts using Semantic Similarity Attention Layer based on BERT
https://github.com/osome-iu/Rematch-RARE
공식 코드https://github.com/overwindows/semanticcodesearch
공식 코드Learning Deep Semantic Model for Code Search using CodeSearchNet Corpus
https://github.com/ozzyou/3d-avs
공식 코드https://github.com/panmani/gccl
공식 코드Graph Component Contrastive Learning for Concept Relatedness Estimation
https://github.com/peluz/beluga
공식 코드Cross-functional Analysis of Generalisation in Behavioural Learning
https://github.com/perceptioncomputinglab/medfilip
공식 코드https://github.com/perceptiveshawty/compcse
공식 코드https://github.com/peteriz/academic-budget-bert
공식 코드https://github.com/phil0212/sgc-net
공식 코드SGC-Net: Stratified Granular Comparison Network for Open-Vocabulary HOI Detection
https://github.com/phmeier/smaragd
공식 코드SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance
https://github.com/pilehvar/deconf
공식 코드https://github.com/pioneer-innovation/zero-shot-object-navigation
공식 코드https://github.com/pkargupta/epimine
공식 코드https://github.com/pkumod/vgstore
공식 코드VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph
https://github.com/platanus-hy/sememes_codriven_text_matching
공식 코드https://github.com/poloclub/neuro-cartography
공식 코드NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
https://github.com/pootiet/augcse
공식 코드AugCSE: Contrastive Sentence Embedding with Diverse Augmentations
https://github.com/poppinace/sapa
공식 코드SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
https://github.com/ppartha03/Semantic-Loss-Dialogue-Generation
공식 코드A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
https://github.com/prashantksharma/CaCD
공식 코드https://github.com/princeton-nlp/SimCSE
공식 코드https://github.com/princeton-nlp/c-sts
공식 코드https://github.com/princeton-nlp/semsup
공식 코드SemSup: Semantic Supervision for Simple and Scalable Zero-shot Generalization
https://github.com/priya22/semantic-textual-relatedness
공식 코드What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study
https://github.com/prometheusXN/D-LADAN
공식 코드Distinguish Confusion in Legal Judgment Prediction via Revised Relation Knowledge
https://github.com/psyonp/accidental_misalignment
공식 코드Accidental Misalignment: Fine-Tuning Language Models Induces Unexpected Vulnerability
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.