Imagen de Portada

Coarse-Tuning for Ad-hoc Document Retrieval Using Pre-trained Language Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Keyaki, Atsushi, Keyaki, Ribeka
Formato:	Preprint
Publicado:	2024
Materias:	Information Retrieval Artificial Intelligence Computation and Language Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models
por: Peng, Zhiyuan, et al.
Publicado: (2023)

RAG System for Supporting Japanese Litigation Procedures: Faithful Response Generation Complying with Legal Norms
por: Ishihara, Yuya, et al.
Publicado: (2025)

Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER
por: Abaho, Micheal, et al.
Publicado: (2024)

Retrieval-augmented Prompt Learning for Pre-trained Foundation Models
por: Chen, Xiang, et al.
Publicado: (2025)

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations
por: Meng, Chuan, et al.
Publicado: (2025)

CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search
por: Wu, Kaixin, et al.
Publicado: (2024)

Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-hoc Retrieval
por: Su, Weihang, et al.
Publicado: (2023)

NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
por: Zeighami, Sepanta, et al.
Publicado: (2024)

InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
por: Wang, Boxin, et al.
Publicado: (2023)

Large Language Model Augmented Exercise Retrieval for Personalized Language Learning
por: Xu, Austin, et al.
Publicado: (2024)

Bottleneck-Minimal Indexing for Generative Document Retrieval
por: Du, Xin, et al.
Publicado: (2024)

Retrieval meets Long Context Large Language Models
por: Xu, Peng, et al.
Publicado: (2023)

ACER: Automatic Language Model Context Extension via Retrieval
por: Gao, Luyu, et al.
Publicado: (2024)

GPT vs RETRO: Exploring the Intersection of Retrieval and Parameter-Efficient Fine-Tuning
por: Ficek, Aleksander, et al.
Publicado: (2024)

Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
por: Shao, Rulin, et al.
Publicado: (2024)

Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models
por: Qiu, Yifu, et al.
Publicado: (2025)

Thesis: Document Summarization with applications to Keyword extraction and Image Retrieval
por: Sundararaj, Jayaprakash
Publicado: (2024)

IRPAPERS: A Visual Document Benchmark for Scientific Retrieval and Question Answering
por: Shorten, Connor, et al.
Publicado: (2026)

MedSlice: Fine-Tuned Large Language Models for Secure Clinical Note Sectioning
por: Davis, Joshua, et al.
Publicado: (2025)

Retrieval Augmented Structured Generation: Business Document Information Extraction As Tool Use
por: Cesista, Franz Louis, et al.
Publicado: (2024)

PromptDSI: Prompt-based Rehearsal-free Continual Learning for Document Retrieval
por: Huynh, Tuan-Luc, et al.
Publicado: (2024)

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
por: Zhang, Xuechen, et al.
Publicado: (2025)

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
por: Xu, Ran, et al.
Publicado: (2024)

Personas within Parameters: Fine-Tuning Small Language Models with Low-Rank Adapters to Mimic User Behaviors
por: Thakur, Himanshu, et al.
Publicado: (2025)

ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance Labeling
por: Zhang, Lingxi, et al.
Publicado: (2024)

Neurosymbolic Retrievers for Retrieval-augmented Generation
por: Saxena, Yash, et al.
Publicado: (2026)

Automated Literature Review Using NLP Techniques and LLM-Based Retrieval-Augmented Generation
por: Ali, Nurshat Fateh, et al.
Publicado: (2024)

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models
por: Taskin, Bilge, et al.
Publicado: (2025)

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation
por: Fang, Haoyang, et al.
Publicado: (2026)

Towards Mixed-Modal Retrieval for Universal Retrieval-Augmented Generation
por: Zhang, Chenghao, et al.
Publicado: (2025)

OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources
por: Baek, Jinheon, et al.
Publicado: (2026)

Explainable Lane Change Prediction for Near-Crash Scenarios Using Knowledge Graph Embeddings and Retrieval Augmented Generation
por: Manzour, M., et al.
Publicado: (2025)

The Chronicles of RAG: The Retriever, the Chunk and the Generator
por: Finardi, Paulo, et al.
Publicado: (2024)

REST: Retrieval-Based Speculative Decoding
por: He, Zhenyu, et al.
Publicado: (2023)

Chain of Retrieval: Multi-Aspect Iterative Search Expansion and Post-Order Search Aggregation for Full Paper Retrieval
por: Park, Sangwoo, et al.
Publicado: (2025)

FIRE: Fact-checking with Iterative Retrieval and Verification
por: Xie, Zhuohan, et al.
Publicado: (2024)

IR2: Information Regularization for Information Retrieval
por: Wang, Jianyou, et al.
Publicado: (2024)

CoRAG: Collaborative Retrieval-Augmented Generation
por: Muhamed, Aashiq, et al.
Publicado: (2025)

ReasonIR: Training Retrievers for Reasoning Tasks
por: Shao, Rulin, et al.
Publicado: (2025)

Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej
por: Nigam, Shubham Kumar, et al.
Publicado: (2025)