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Sentence Embeddings
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
CTRLStruct: Dialogue Structure Learning for Open-Domain Response Generation
Weighted Sampling for Masked Language Modeling
NoPPA: Non-Parametric Pairwise Attention Random Walk Model for Sentence Representation
SkillRec: A Data-Driven Approach to Job Skill Recommendation for Career Insights
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE
LEALLA: Learning Lightweight Language-agnostic Sentence Embeddings with Knowledge Distillation
Investigating the Effect of Relative Positional Embeddings on AMR-to-Text Generation with Structural Adapters
Efficient and Flexible Topic Modeling using Pretrained Embeddings and Bag of Sentences
Representation biases in sentence transformers
Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings
Keyword Embeddings for Query Suggestion
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its Applications
SAIDS: A Novel Approach for Sentiment Analysis Informed of Dialect and Sarcasm
Topic Segmentation Model Focusing on Local Context
Improving Continuous Sign Language Recognition with Consistency Constraints and Signer Removal
Relational Sentence Embedding for Flexible Semantic Matching
MED-SE: Medical Entity Definition-based Sentence Embedding
Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation
CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation
T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation
Zero-Shot Learning for Joint Intent and Slot Labeling
L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi
Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval
Imagination is All You Need! Curved Contrastive Learning for Abstract Sequence Modeling Utilized on Long Short-Term Dialogue Planning
English Contrastive Learning Can Learn Universal Cross-lingual Sentence Embeddings
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
Unsupervised Extractive Summarization with Heterogeneous Graph Embeddings for Chinese Document
miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
Preserving Semantics in Textual Adversarial Attacks
Contrastive Learning with Prompt-derived Virtual Semantic Prototypes for Unsupervised Sentence Embedding
Using Large Pre-Trained Language Model to Assist FDA in Premarket Medical Device
Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection
Very Low Resource Sentence Alignment: Luhya and Swahili
Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations
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