Semantic Textual Similarity
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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/binwang28/evalrank-embedding-evaluation
공식 코드Just Rank: Rethinking Evaluation with Word and Sentence Similarities
https://github.com/binwang28/rse
공식 코드Relational Sentence Embedding for Flexible Semantic Matching
https://github.com/bio-ontology-research-group/opa2vec
공식 코드https://github.com/blurryface0814/pcpnet
공식 코드PCPNet: An Efficient and Semantic-Enhanced Transformer Network for Point Cloud Prediction
https://github.com/bohanli/BERT-flow
공식 코드https://github.com/boleima/profit
공식 코드https://github.com/boracaglayan/bis-nl2sql
공식 코드BIS: NL2SQL Service Evaluation Benchmark for Business Intelligence Scenarios
https://github.com/brandeis-llc/L-CSTS
공식 코드https://github.com/bravegroup/psps
공식 코드https://github.com/buraksatar/RoME_video_retrieval
공식 코드https://github.com/cambridgeltl/mirror-bert
공식 코드https://github.com/camma-public/surglatentgraph
공식 코드Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning
https://github.com/casperhansen/PairRec
공식 코드https://github.com/catrin-baze/ino-of-factify
공식 코드INO at Factify 2: Structure Coherence based Multi-Modal Fact Verification
https://github.com/ccilab-doshisha/sdjc
공식 코드https://github.com/cedricdeboom/RepresentationLearning
공식 코드Representation learning for very short texts using weighted word embedding aggregation
https://github.com/cgnorthcutt/forum-diversification
공식 코드https://github.com/cgshpi/topic-models-and-dimensionality-reduction-benchmark
공식 코드https://github.com/chaojiang06/wiki-auto
공식 코드Neural CRF Model for Sentence Alignment in Text Simplification
https://github.com/chendelong1999/linguistic-similarity
공식 코드Linguistic Minimal Pairs Elicit Linguistic Similarity in Large Language Models
https://github.com/chuzhumin98/convsearch-dataset
공식 코드Towards Better Understanding of User Satisfaction in Open-Domain Conversational Search
https://github.com/cjf00000/StatQuant
공식 코드A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
https://github.com/claudiashu/una
공식 코드Unsupervised hard Negative Augmentation for contrastive learning
https://github.com/cleopatra-itn/claim_detection
공식 코드https://github.com/clovaai/symmetrical-synthesis
공식 코드https://github.com/cluebbers/dpo-rlhf-paraphrase-types
공식 코드Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked Data
https://github.com/colinlu50/hydratext
공식 코드Effective and Imperceptible Adversarial Textual Attack via Multi-objectivization
https://github.com/cpjku/performance_embeddings_fire23
공식 코드https://github.com/csong27/collision-bert
공식 코드https://github.com/cuiniki/llms-are-not-scorers
공식 코드LLMs Are Not Scorers: Rethinking MT Evaluation with Generation-Based Methods
https://github.com/cvjena/semantic-embeddings
공식 코드Hierarchy-based Image Embeddings for Semantic Image Retrieval
https://github.com/cycraft-corp/CmdCaliper
공식 코드CmdCaliper: A Semantic-Aware Command-Line Embedding Model and Dataset for Security Research
https://github.com/cyr19/menli
공식 코드MENLI: Robust Evaluation Metrics from Natural Language Inference
https://github.com/daiyongya/markbert
공식 코드https://github.com/danieljunior/jidm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.