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

Showing 110 of 2381 papers

TitleStatusHype
SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts0
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression0
FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution DetectionCode0
LineRetriever: Planning-Aware Observation Reduction for Web Agents0
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning0
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval0
Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models0
Intrinsic vs. Extrinsic Evaluation of Czech Sentence Embeddings: Semantic Relevance Doesn't Help with MT Evaluation0
PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty0
Semantic similarity estimation for domain specific data using BERT and other techniques0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SMARTRoBERTaDev Pearson Correlation92.8Unverified
2DeBERTa (large)Accuracy92.5Unverified
3SMART-BERTDev Pearson Correlation90Unverified
4MT-DNN-SMARTPearson Correlation0.93Unverified
5StructBERTRoBERTa ensemblePearson Correlation0.93Unverified
6Mnet-SimPearson Correlation0.93Unverified
7XLNet (single model)Pearson Correlation0.93Unverified
8ALBERTPearson Correlation0.93Unverified
9T5-11BPearson Correlation0.93Unverified
10RoBERTaPearson Correlation0.92Unverified