SOTAVerified

Semantic Textual Similarity

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

Papers

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Showing 1–10 of 2381 papers

TitleStatusHype
SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts—0
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression—0
FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution DetectionCode0
LineRetriever: Planning-Aware Observation Reduction for Web Agents—0
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning—0
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval—0
Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models—0
Intrinsic vs. Extrinsic Evaluation of Czech Sentence Embeddings: Semantic Relevance Doesn't Help with MT Evaluation—0
PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty—0
Semantic similarity estimation for domain specific data using BERT and other techniques—0
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All datasetsSTS BenchmarkMTEBMRPCSICKSTS13STS14STS12STS15STS16MRPC DevSentEvalSICK-R

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Synthesizer (R+V)Accuracy91.2—Unverified
2TinyBERT-6 67MAccuracy86.3—Unverified