Semantic Textual Similarity
556 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
Libraries
Use these libraries to find Semantic Textual Similarity models and implementationsLatest papers
A Collection of Pragmatic-Similarity Judgments over Spoken Dialog Utterances
While there exist measures for semantic similarity and prosodic similarity, there are as yet none for pragmatic similarity.
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval
To achieve this, we propose L2RM, a general framework based on Optimal Transport (OT) that learns to rematch mismatched pairs.
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt Denoising
Recently, promptable segmentation models, such as the Segment Anything Model (SAM), have demonstrated robust zero-shot generalization capabilities on static images.
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation
Semantic segmentation has innately relied on extensive pixel-level annotated data, leading to the emergence of unsupervised methodologies.
NextLevelBERT: Investigating Masked Language Modeling with Higher-Level Representations for Long Documents
While (large) language models have significantly improved over the last years, they still struggle to sensibly process long sequences found, e. g., in books, due to the quadratic scaling of the underlying attention mechanism.
The Impact of Word Splitting on the Semantic Content of Contextualized Word Representations
When deriving contextualized word representations from language models, a decision needs to be made on how to obtain one for out-of-vocabulary (OOV) words that are segmented into subwords.
DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain
This limitation hampers the evaluation of the latest French biomedical models, as they are either assessed on a minimal number of tasks with non-standardized protocols or evaluated using general downstream tasks.
UMBCLU at SemEval-2024 Task 1A and 1C: Semantic Textual Relatedness with and without machine translation
The aim of SemEval-2024 Task 1, "Semantic Textual Relatedness for African and Asian Languages" is to develop models for identifying semantic textual relatedness (STR) between two sentences using multiple languages (14 African and Asian languages) and settings (supervised, unsupervised, and cross-lingual).
Semantic Textual Similarity Assessment in Chest X-ray Reports Using a Domain-Specific Cosine-Based Metric
Medical language processing and deep learning techniques have emerged as critical tools for improving healthcare, particularly in the analysis of medical imaging and medical text data.
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages
Exploring and quantifying semantic relatedness is central to representing language.