Semantic Textual Similarity
557 papers with code • 13 benchmarks • 17 datasets
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
Benchmarks
These leaderboards are used to track progress in Semantic Textual Similarity
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Libraries
Use these libraries to find Semantic Textual Similarity models and implementations
GLUE
MRPC
SICK
SentEval
CARER
MTEB
STS Benchmark
EVALution
CxC
Latest papers with no code
DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment
Most of the existing works focus on improving the representation ability for the contextualized embedding of the [CLS] token and calculate relevance using textual semantic similarity.
Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language
The latest advancements in machine learning and deep learning have brought forth the concept of semantic similarity, which has proven immensely beneficial in multiple applications and has largely replaced keyword search.
Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models
Subsequently, ESREAL computes token-level hallucination scores by assessing the semantic similarity of aligned regions based on the type of hallucination.
Connecting the Dots: Inferring Patent Phrase Similarity with Retrieved Phrase Graphs
We study the patent phrase similarity inference task, which measures the semantic similarity between two patent phrases.
Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives
In this paper, we introduce the Financial-STS task, a financial domain-specific NLP task designed to measure the nuanced semantic similarity between pairs of financial narratives.
RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning
In this paper, we introduce RobustSentEmbed, a self-supervised sentence embedding framework designed to improve both generalization and robustness in diverse text representation tasks and against a diverse set of adversarial attacks.
A Modified Word Saliency-Based Adversarial Attack on Text Classification Models
This paper introduces a novel adversarial attack method targeting text classification models, termed the Modified Word Saliency-based Adversarial At-tack (MWSAA).
SIFiD: Reassess Summary Factual Inconsistency Detection with LLM
Ensuring factual consistency between the summary and the original document is paramount in summarization tasks.
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach
We also share our experience in deploying COLA in our real-world cloud system, Cloud X.
Deep Contrastive Multi-view Clustering under Semantic Feature Guidance
To mitigate the interference of view-private information, specific view and fusion view semantic features are learned by cluster-level contrastive learning and concatenated to measure the semantic similarity of instances.
