Image de couverture de livre

Identifying Key Terms in Prompts for Relevance Evaluation with GPT Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Choi, Jaekeol
Format:	Preprint
Publié:	2024
Sujets:	Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Identifying Key Terms in Prompts for Relevance Evaluation with GPT Models
par: Jaekeol, Choi
Publié: (2026)

Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
par: Zhou, Jianqun, et autres
Publié: (2024)

Topic-Specific Classifiers are Better Relevance Judges than Prompted LLMs
par: Gienapp, Lukas, et autres
Publié: (2025)

The Cranfield II Relevance Assessments: A Critical Evaluation
par: Harter, Stephen P.
Publié: (1971)

Limitations of Automatic Relevance Assessments with Large Language Models for Fair and Reliable Retrieval Evaluation
par: Otero, David, et autres
Publié: (2024)

LLMs Can Patch Up Missing Relevance Judgments in Evaluation
par: Upadhyay, Shivani, et autres
Publié: (2024)

An Exam-based Evaluation Approach Beyond Traditional Relevance Judgments
par: Farzi, Naghmeh, et autres
Publié: (2024)

Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
par: Rampisela, Theresia Veronika, et autres
Publié: (2025)

Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
par: Chen, Zeyuan, et autres
Publié: (2024)

Metamorphic Evaluation of ChatGPT as a Recommender System
par: Khirbat, Madhurima, et autres
Publié: (2024)

Unleashing the Native Recommendation Potential: LLM-Based Generative Recommendation via Structured Term Identifiers
par: Zhang, Zhiyang, et autres
Publié: (2026)

Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance
par: Rampisela, Theresia Veronika, et autres
Publié: (2024)

Do LLM-judges Align with Human Relevance in Cranfield-style Recommender Evaluation?
par: Penha, Gustavo, et autres
Publié: (2025)

FGR-ColBERT: Identifying Fine-Grained Relevance Tokens During Retrieval
par: Jarolím, Antonín, et autres
Publié: (2026)

Exploring Large Language Models for Relevance Judgments in Tetun
par: de Jesus, Gabriel, et autres
Publié: (2024)

Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models
par: Parry, Andrew, et autres
Publié: (2024)

Multi-stage Large Language Model Pipelines Can Outperform GPT-4o in Relevance Assessment
par: Schnabel, Julian A., et autres
Publié: (2025)

REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking
par: Wang, Pinhuan, et autres
Publié: (2025)

HCMRM: A High-Consistency Multimodal Relevance Model for Search Ads
par: Gan, Guobing, et autres
Publié: (2025)

LLMJudge: LLMs for Relevance Judgments
par: Rahmani, Hossein A., et autres
Publié: (2024)

Generalized Pseudo-Relevance Feedback
par: Tu, Yiteng, et autres
Publié: (2025)

A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment
par: Arabzadeh, Negar, et autres
Publié: (2025)

RecGPT: A Foundation Model for Sequential Recommendation
par: Jiang, Yangqin, et autres
Publié: (2025)

Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awareness
par: Zhao, Xinran, et autres
Publié: (2024)

Axiomatic Causal Interventions for Reverse Engineering Relevance Computation in Neural Retrieval Models
par: Chen, Catherine, et autres
Publié: (2024)

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing
par: Yan, Le, et autres
Publié: (2024)

Discovering Biases in Information Retrieval Models Using Relevance Thesaurus as Global Explanation
par: Kim, Youngwoo, et autres
Publié: (2024)

Impact of Shallow vs. Deep Relevance Judgments on BERT-based Reranking Models
par: Iturra-Bocaz, Gabriel, et autres
Publié: (2025)

RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
par: Han, Haoyu, et autres
Publié: (2025)

LLM-Assisted Pseudo-Relevance Feedback
par: Otero, David, et autres
Publié: (2026)

LUCid: Redefining Relevance For Lifelong Personalization
par: Okite, Chimaobi, et autres
Publié: (2026)

TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval
par: Li, Hang, et autres
Publié: (2024)

MemConflict: Evaluating Long-Term Memory Systems Under Memory Conflicts
par: Tao, Zhen, et autres
Publié: (2026)

UQABench: Evaluating User Embedding for Prompting LLMs in Personalized Question Answering
par: Liu, Langming, et autres
Publié: (2025)

Impact and Relevance of Cognition Journal in the Field of Cognitive Science: An Evaluation
par: Batcha, M Sadik, et autres
Publié: (2025)

Augmenting Sequential Recommendation with Balanced Relevance and Diversity
par: Dang, Yizhou, et autres
Publié: (2024)

Generative Retrieval Meets Multi-Graded Relevance
par: Tang, Yubao, et autres
Publié: (2024)

Don't Use LLMs to Make Relevance Judgments
par: Soboroff, Ian
Publié: (2024)

Is Relevance Propagated from Retriever to Generator in RAG?
par: Tian, Fangzheng, et autres
Publié: (2025)

Migrating a Job Search Relevance Function
par: Mountain, Bennett, et autres
Publié: (2025)