Image de couverture de livre

Semantic Novelty Trajectories in 80,000 Books: A Cross-Corpus Embedding Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Zimmerman, Fred
Format:	Preprint
Publié:	2026
Sujets:	Computation and Language Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Large-Scale, Cross-Disciplinary Corpus of Systematic Reviews
par: Achkar, Pierre, et autres
Publié: (2026)

Zero-Shot Contextual Embeddings via Offline Synthetic Corpus Generation
par: Lippmann, Philip, et autres
Publié: (2025)

Narrative Fingerprints: Multi-Scale Author Identification via Novelty Curve Dynamics
par: Zimmerman, Fred, et autres
Publié: (2026)

OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment
par: Zhang, Ming, et autres
Publié: (2026)

GraphMind: Interactive Novelty Assessment System for Accelerating Scientific Discovery
par: da Silva, Italo Luis, et autres
Publié: (2025)

Llama-Embed-Nemotron-8B: A Universal Text Embedding Model for Multilingual and Cross-Lingual Tasks
par: Babakhin, Yauhen, et autres
Publié: (2025)

CorpusLM: Towards a Unified Language Model on Corpus for Knowledge-Intensive Tasks
par: Li, Xiaoxi, et autres
Publié: (2024)

Can Cross Encoders Produce Useful Sentence Embeddings?
par: Ananthakrishnan, Haritha, et autres
Publié: (2025)

Pooling and Semantic Shift: The Fundamental Challenges in Long Text Embedding and Retrieval
par: Gao, Hang, et autres
Publié: (2026)

LEMUR: A Corpus for Robust Fine-Tuning of Multilingual Law Embedding Models for Retrieval
par: Ahmadi, Narges Baba, et autres
Publié: (2026)

Beyond Single-Dimension Novelty: How Combinations of Theory, Method, and Results-based Novelty Shape Scientific Impact
par: Zhao, Yi, et autres
Publié: (2026)

Semantic Certainty Assessment in Vector Retrieval Systems: A Novel Framework for Embedding Quality Evaluation
par: Du, Y.
Publié: (2025)

LLM-based Embeddings: Attention Values Encode Sentence Semantics Better Than Hidden States
par: Zhang, Yeqin, et autres
Publié: (2026)

Corpus-Steered Query Expansion with Large Language Models
par: Lei, Yibin, et autres
Publié: (2024)

Unsupervised Corpus Poisoning Attacks in Continuous Space for Dense Retrieval
par: Li, Yongkang, et autres
Publié: (2025)

Reproducing HotFlip for Corpus Poisoning Attacks in Dense Retrieval
par: Li, Yongkang, et autres
Publié: (2025)

BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model
par: Zhiyuli, Aakas, et autres
Publié: (2023)

Exploring Diversity, Novelty, and Popularity Bias in ChatGPT's Recommendations
par: Di Palma, Dario, et autres
Publié: (2026)

Constructing Cross-lingual Consumer Health Vocabulary with Word-Embedding from Comparable User Generated Content
par: Chang, Chia-Hsuan, et autres
Publié: (2022)

CorpusBrain++: A Continual Generative Pre-Training Framework for Knowledge-Intensive Language Tasks
par: Guo, Jiafeng, et autres
Publié: (2024)

Applying Text Embedding Models for Efficient Analysis in Labeled Property Graphs
par: Podstawski, Michal
Publié: (2025)

Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval
par: Knappich, Valentin, et autres
Publié: (2026)

SemCORE: A Semantic-Enhanced Generative Cross-Modal Retrieval Framework with MLLMs
par: Li, Haoxuan, et autres
Publié: (2025)

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding
par: Qiang, Minjie, et autres
Publié: (2026)

TurkEmbed: Turkish Embedding Model on NLI & STS Tasks
par: Ezerceli, Özay, et autres
Publié: (2025)

PatentEdits: Framing Patent Novelty as Textual Entailment
par: Lee, Ryan, et autres
Publié: (2024)

Corpus-Based Approaches to Igbo Diacritic Restoration
par: Ezeani, Ignatius
Publié: (2026)

Rethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"
par: Seputis, Dominykas, et autres
Publié: (2025)

ReasonEmbed: Enhanced Text Embeddings for Reasoning-Intensive Document Retrieval
par: Chen, Jianlyu, et autres
Publié: (2025)

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
par: Min, Dehai, et autres
Publié: (2025)

What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty
par: Zhang, Bowei, et autres
Publié: (2025)

Comparative Analysis of Document-Level Embedding Methods for Similarity Scoring on Shakespeare Sonnets and Taylor Swift Lyrics
par: Kramer, Klara
Publié: (2024)

Granite Embedding Models
par: Awasthy, Parul, et autres
Publié: (2025)

Back-of-the-Book Index Automation for Arabic Documents
par: Haidar, Nawal, et autres
Publié: (2024)

ChEmbed: Enhancing Chemical Literature Search Through Domain-Specific Text Embeddings
par: Kasmaee, Ali Shiraee, et autres
Publié: (2025)

Multilingual E5 Text Embeddings: A Technical Report
par: Wang, Liang, et autres
Publié: (2024)

A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering
par: Krishnamurthy, Madan, et autres
Publié: (2025)

Granite Embedding R2 Models
par: Awasthy, Parul, et autres
Publié: (2025)

An Open-Source Dual-Loss Embedding Model for Semantic Retrieval in Higher Education
par: Sajja, Ramteja, et autres
Publié: (2025)

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning
par: Sun, Yiqun, et autres
Publié: (2025)