Cover Image

Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Knappich, Valentin, Hätty, Anna, Razniewski, Simon, Friedrich, Annemarie
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs
by: Knappich, Valentin, et al.
Published: (2024)

PEDANTIC: A Dataset for the Automatic Examination of Definiteness in Patent Claims
by: Knappich, Valentin, et al.
Published: (2025)

PatentEdits: Framing Patent Novelty as Textual Entailment
by: Lee, Ryan, et al.
Published: (2024)

Spectral Tempering for Embedding Compression in Dense Passage Retrieval
by: Li, Yongkang, et al.
Published: (2026)

OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment
by: Zhang, Ming, et al.
Published: (2026)

Fine-Grained Table Retrieval Through the Lens of Complex Queries
by: Kosiuk, Wojciech, et al.
Published: (2026)

Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents
by: Singhania, Sneha, et al.
Published: (2024)

Distilling a Small Utility-Based Passage Selector to Enhance Retrieval-Augmented Generation
by: Zhang, Hengran, et al.
Published: (2025)

Exploring Diversity, Novelty, and Popularity Bias in ChatGPT's Recommendations
by: Di Palma, Dario, et al.
Published: (2026)

Automated Neural Patent Landscaping in the Small Data Regime
by: Erana, Tisa Islam, et al.
Published: (2024)

Going over Fine Web with a Fine-Tooth Comb: Technical Report of Indexing Fine Web for Problematic Content Search and Retrieval
by: Marinas, Inés Altemir, et al.
Published: (2025)

What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty
by: Zhang, Bowei, et al.
Published: (2025)

Patent Novelty Assessment Accelerating Innovation and Patent Prosecution
by: Kashyap, Kapil, et al.
Published: (2025)

Exploring Optimal Transport-Based Multi-Grained Alignments for Text-Molecule Retrieval
by: Min, Zijun, et al.
Published: (2024)

LEMUR: A Corpus for Robust Fine-Tuning of Multilingual Law Embedding Models for Retrieval
by: Ahmadi, Narges Baba, et al.
Published: (2026)

FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAG
by: Hong, Yubin, et al.
Published: (2025)

Knowledge Compression via Question Generation: Enhancing Multihop Document Retrieval without Fine-tuning
by: Eponon, Anvi Alex, et al.
Published: (2025)

RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation
by: Li, Xiaoxi, et al.
Published: (2024)

ConQRet: Benchmarking Fine-Grained Evaluation of Retrieval Augmented Argumentation with LLM Judges
by: Dhole, Kaustubh D., et al.
Published: (2024)

Multilingual Information Retrieval with a Monolingual Knowledge Base
by: Zhuang, Yingying, et al.
Published: (2025)

Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers
by: Sawarkar, Kunal, et al.
Published: (2024)

Scientific Paper Retrieval with LLM-Guided Semantic-Based Ranking
by: Zhang, Yunyi, et al.
Published: (2025)

L-RAG: Balancing Context and Retrieval with Entropy-Based Lazy Loading
by: Voloshyn, Sergii
Published: (2026)

Retrieval Augmented Generation-Based Incident Resolution Recommendation System for IT Support
by: Isaza, Paulina Toro, et al.
Published: (2024)

Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
by: Wang, Haoyu, et al.
Published: (2025)

Dense Passage Retrieval: Is it Retrieving?
by: Reichman, Benjamin, et al.
Published: (2024)

RARe: Retrieval Augmented Retrieval with In-Context Examples
by: Tejaswi, Atula, et al.
Published: (2024)

Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications
by: Lin, Ethan, et al.
Published: (2024)

ClusterRAG: Cluster-Based Collaborative Filtering for Personalized Retrieval-Augmented Generation
by: Nkhata, Gibson, et al.
Published: (2026)

Bridge-RAG: An Abstract Bridge Tree Based Retrieval Augmented Generation Algorithm
by: Li, Zihang, et al.
Published: (2026)

A Diverse and Effective Retrieval-Based Debt Collection System with Expert Knowledge
by: Luo, Jiaming, et al.
Published: (2025)

MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval
by: Khanghah, Kiarash Naghavi, et al.
Published: (2026)

Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary?
by: Jedidi, Nour, et al.
Published: (2025)

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
by: Jin, Bowen, et al.
Published: (2025)

Benchmarking Information Retrieval Models on Complex Retrieval Tasks
by: Killingback, Julian, et al.
Published: (2025)

Utility-Focused LLM Annotation for Retrieval and Retrieval-Augmented Generation
by: Zhang, Hengran, et al.
Published: (2025)

Leveraging the Power of LLMs: A Fine-Tuning Approach for High-Quality Aspect-Based Summarization
by: Mullick, Ankan, et al.
Published: (2024)

NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment
by: Wu, Wenqing, et al.
Published: (2026)

FinRetrieval: A Benchmark for Financial Data Retrieval by AI Agents
by: Kim, Eric Y., et al.
Published: (2026)

Dense X Retrieval: What Retrieval Granularity Should We Use?
by: Chen, Tong, et al.
Published: (2023)