Semantic Textual Similarity
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Benchmarks
STS Benchmark
MRPC
MTEB
SICK
STS13
STS14
STS12
STS15
STS16
SentEval
CxC
MRPC Dev
SICK-R
Most implemented
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Papers
The Embedder's Dilemma: LLMs Are Better, but at What Cost?
Should you replace your text-embedding pipeline with a large language model? We answer this with a controlled, cost-aware comparison of ten LLMs across six families and 26 embedding models (118M to 14B parameters) on 37 …
Semantic Textual SimilarityMitigating Scoring Bias in LLM-as-a-Judge via Random Number Generation
Large Language Models (LLMs) are often used as evaluators of text quality, known as LLM-as-a-Judge, which can outperform conventional automatic evaluation metrics that rely on reference texts. However, LLM evaluators ten…
Semantic Textual SimilarityMTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese
Text embeddings for Portuguese have no dedicated benchmark: evaluation rests on translated corpora such as English MS MARCO or on thin multilingual coverage, with native tasks scattered and unconsolidated. We introduce M…
Semantic Textual SimilarityBeyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders
Portuguese remains underrepresented in text embedding evaluation, despite being one of the most widely spoken languages in the world. As a result, embedding models are often selected based on English or multilingual metr…
Semantic Textual SimilarityRepresentation LearningDySem: Uncovering Dynamic Semantic Components of Large Language Models for Calculating Semantic Textual Similarity
Calculating semantic textual similarity is a foundational task in natural language processing. Current large language models (LLMs) based methods typically rely on extracting last-layer hidden states with fixed dimension…
Semantic Textual SimilaritySemantic SimilarityGeneral KnowledgeMATCHA: Matching Text via Contrastive Semantic Alignment
Reliable evaluation is essential for understanding large language model (LLM) performance, yet today's go-to metrics, namely token-overlap scores (e.g., ROUGE) and embedding-based measures (e.g., BERTScore), often misjud…
Semantic Textual SimilarityNatural Language InferenceSemantic Similarity