SOTAVerified

Document Embedding

Papers

Showing 1–50 of 78 papers

TitleStatusHype
BERTopic: Neural topic modeling with a class-based TF-IDF procedureCode5
QAEncoder: Towards Aligned Representation Learning in Question Answering SystemCode2
ARAGOG: Advanced RAG Output GradingCode2
HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text ClassificationCode1
Neighborhood Contrastive Learning for Scientific Document Representations with Citation EmbeddingsCode1
MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase ExtractionCode1
Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global ContextCode1
AC-LoRA: (Almost) Training-Free Access Control-Aware Multi-Modal LLMs—0
BERTopic for Topic Modeling of Hindi Short Texts: A Comparative Study—0
Trajectories of Change: Approaches for Tracking Knowledge Evolution—0
Enhancing Question Answering Precision with Optimized Vector Retrieval and Instructions—0
Contextual Document Embeddings—0
DocNet: Semantic Structure in Inductive Bias Detection Models—0
rollama: An R package for using generative large language models through Ollama—0
Word Embeddings Revisited: Do LLMs Offer Something New?—0
KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering—0
Facilitating Interdisciplinary Knowledge Transfer with Research Paper Recommender SystemsCode0
A Novel Method of Fuzzy Topic Modeling based on Transformer Processing—0
Shuffle & Divide: Contrastive Learning for Long Text—0
Caching Historical Embeddings in Conversational Search—0
LEA: Meta Knowledge-Driven Self-Attentive Document Embedding for Few-Shot Text Classification—0
Assessing the trade-off between prediction accuracy and interpretability for topic modeling on energetic materials corpora—0
Approach to Predicting News -- A Precise Multi-LSTM Network With BERTCode0
Academic Resource Text Level Multi-label Classification based on Attention—0
CODER: An efficient framework for improving retrieval through COntextual Document Embedding RerankingCode0
Sentiment Analysis on Brazilian Portuguese User Reviews—0
CAWESumm: A Contextual and Anonymous Walk Embedding Based Extractive Summarization of Legal Bills—0
MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction—0
JOINTLY LEARNING TOPIC SPECIFIC WORD AND DOCUMENT EMBEDDING—0
College Student Retention Risk Analysis From Educational Database using Multi-Task Multi-Modal Neural Fusion—0
Academic Expert Finding via (k,P)-Core based Embedding over Heterogeneous Graphs—0
Document Embedding for Scientific Articles: Efficacy of Word Embeddings vs TFIDF—0
Hi-Transformer: Hierarchical Interactive Transformer for Efficient and Effective Long Document Modeling—0
Multifaceted Domain-Specific Document EmbeddingsCode0
Evaluation of Field-Aware Neural Ranking Models for Recipe Search—0
Unsupervised Document Embedding via Contrastive Augmentation—0
HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions—0
Transformer based Multilingual document Embedding model—0
Improve Document Embedding for Text Categorization Through Deep Siamese Neural Network—0
SueNes: A Weakly Supervised Approach to Evaluating Single-Document Summarization via Negative SamplingCode0
NUIG at TIAD: Combining Unsupervised NLP and Graph Metrics for Translation Inference—0
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural NetworksCode0
Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding—0
Can x2vec Save Lives? Integrating Graph and Language Embeddings for Automatic Mental Health ClassificationCode0
Long-length Legal Document Classification—0
Doc2Vec on the PubMed corpus: study of a new approach to generate related articles—0
Discovering topics with neural topic models built from PLSA assumptions—0
Discovering Topics With Neural Topic Models Built From PLSA Loss—0
Neural Embedding Allocation: Distributed Representations of Topic Models—0
Evaluating the Utility of Document Embedding Vector Difference for Relation Learning—0
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