Cover Image

Tailoring Table Retrieval from a Field-aware Hybrid Matching Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Da, Bi, Keping, Guo, Jiafeng, Cheng, Xueqi
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bridging Queries and Tables through Entities in Table Retrieval
by: Li, Da, et al.
Published: (2025)

Reproducibility Analysis and Enhancements for Multi-Aspect Dense Retriever with Aspect Learning
by: Bi, Keping, et al.
Published: (2024)

CIR at the NTCIR-17 ULTRE-2 Task
by: Yu, Lulu, et al.
Published: (2023)

Data, Not Model: Explaining Bias toward LLM Texts in Neural Retrievers
by: Huang, Wei, et al.
Published: (2026)

How Do LLM-Generated Texts Impact Term-Based Retrieval Models?
by: Huang, Wei, et al.
Published: (2025)

LLM-Specific Utility: A New Perspective for Retrieval-Augmented Generation
by: Zhang, Hengran, et al.
Published: (2025)

An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs
by: Zhang, Hengran, et al.
Published: (2024)

Unbiased Learning to Rank with Query-Level Click Propensity Estimation: Beyond Pointwise Observation and Relevance
by: Yu, Lulu, et al.
Published: (2025)

A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval
by: Sun, Xiaojie, et al.
Published: (2023)

Training Dense Retrievers with Multiple Positive Passages
by: Wang, Benben, et al.
Published: (2026)

Injecting External Knowledge into the Reasoning Process Enhances Retrieval-Augmented Generation
by: Tang, Minghao, et al.
Published: (2025)

A Comparative Study of Specialized LLMs as Dense Retrievers
by: Zhang, Hengran, et al.
Published: (2025)

Can LLM Annotations Replace User Clicks for Learning to Rank?
by: Yu, Lulu, et al.
Published: (2025)

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

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

Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling
by: Zhang, Hengran, et al.
Published: (2025)

Beyond Relevance: Utility-Centric Retrieval in the LLM Era
by: Zhang, Hengran, et al.
Published: (2026)

Contextual Dual Learning Algorithm with Listwise Distillation for Unbiased Learning to Rank
by: Yu, Lulu, et al.
Published: (2024)

Does Generative Retrieval Overcome the Limitations of Dense Retrieval?
by: Zhang, Yingchen, et al.
Published: (2025)

Bagging-Based Model Merging for Robust General Text Embeddings
by: Zhang, Hengran, et al.
Published: (2026)

LifeIR at the NTCIR-18 Lifelog-6 Task
by: Chen, Jiahan, et al.
Published: (2025)

On the Scaling of Robustness and Effectiveness in Dense Retrieval
by: Liu, Yu-An, et al.
Published: (2025)

On the Robustness of Generative Information Retrieval Models
by: Liu, Yu-An, et al.
Published: (2024)

Listwise Generative Retrieval Models via a Sequential Learning Process
by: Tang, Yubao, et al.
Published: (2024)

Generative Retrieval Meets Multi-Graded Relevance
by: Tang, Yubao, et al.
Published: (2024)

From Relevance to Utility: Evidence Retrieval with Feedback for Fact Verification
by: Zhang, Hengran, et al.
Published: (2023)

Bootstrapped Pre-training with Dynamic Identifier Prediction for Generative Retrieval
by: Tang, Yubao, et al.
Published: (2024)

A Generative Framework for Personalized Sticker Retrieval
by: Zhou, Changjiang, et al.
Published: (2025)

Continual Learning for Generative Retrieval over Dynamic Corpora
by: Chen, Jiangui, et al.
Published: (2023)

VeriCite: Towards Reliable Citations in Retrieval-Augmented Generation via Rigorous Verification
by: Qian, Haosheng, et al.
Published: (2025)

AdversarialCoT: Single-Document Retrieval Poisoning for LLM Reasoning
by: Song, Hongru, et al.
Published: (2026)

TrustRAG: An Information Assistant with Retrieval Augmented Generation
by: Fan, Yixing, et al.
Published: (2025)

Generative Retrieval for Book search
by: Tang, Yubao, et al.
Published: (2025)

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding
by: Li, Da, et al.
Published: (2025)

Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective
by: Liu, Yu-An, et al.
Published: (2024)

The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems
by: Song, Hongru, et al.
Published: (2025)

LLMs as Sparse Retrievers:A Framework for First-Stage Product Search
by: Song, Hongru, et al.
Published: (2025)

Reconstructing Content via Collaborative Attention to Improve Multimodal Embedding Quality
by: Chen, Jiahan, et al.
Published: (2026)

RouteRAG: Efficient Retrieval-Augmented Generation from Text and Graph via Reinforcement Learning
by: Guo, Yucan, et al.
Published: (2025)

Event-aware Video Corpus Moment Retrieval
by: Hou, Danyang, et al.
Published: (2024)