Document Ranking

56 papers with code • 2 benchmarks • 6 datasets

Sort documents according to some criterion so that the "best" results appear early in the result list displayed to the user (Source: Wikipedia).

Libraries

Use these libraries to find Document Ranking models and implementations
3 papers
209
3 papers
209

Query Augmentation by Decoding Semantics from Brain Signals

yeziyi1998/brain-query-augmentation 24 Feb 2024

If the quality of the initially retrieved documents is low, then the effectiveness of query augmentation would be limited as well.

1
24 Feb 2024

Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from Large Language Models

pxyu/llm-nle-for-calibration 19 Feb 2024

The process of scale calibration in ranking systems involves adjusting the outputs of rankers to correspond with significant qualities like click-through rates or relevance, crucial for mirroring real-world value and thereby boosting the system's effectiveness and reliability.

1
19 Feb 2024

Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking

ielab/llm-qlm 20 Oct 2023

In the field of information retrieval, Query Likelihood Models (QLMs) rank documents based on the probability of generating the query given the content of a document.

9
20 Oct 2023

A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models

ielab/llm-rankers 14 Oct 2023

Our approach reduces the number of LLM inferences and the amount of prompt token consumption during the ranking procedure, significantly improving the efficiency of LLM-based zero-shot ranking.

37
14 Oct 2023

Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking

lixsh6/tencent_wsdm_cup2023 27 Feb 2023

Pre-trained language models have achieved great success in various large-scale information retrieval tasks.

19
27 Feb 2023

LEAD: Liberal Feature-based Distillation for Dense Retrieval

microsoft/simxns 10 Dec 2022

Knowledge distillation is often used to transfer knowledge from a strong teacher model to a relatively weak student model.

98
10 Dec 2022

Principled Multi-Aspect Evaluation Measures of Rankings

lcschv/toma 1 Dec 2022

Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query.

1
01 Dec 2022

Enhancing User Behavior Sequence Modeling by Generative Tasks for Session Search

haon-chen/ase-official 23 Aug 2022

To help the encoding of the current user behavior sequence, we propose to use a decoder and the information of future sequences and a supplemental query.

1
23 Aug 2022

From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document Ranking

daod/dcl 22 Aug 2022

In this work, we propose a curriculum learning framework for context-aware document ranking, in which the ranking model learns matching signals between the search context and the candidate document in an easy-to-hard manner.

13
22 Aug 2022

Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding

oaqa/FlexNeuART 4 Jul 2022

Most other models had poor zero-shot performance (sometimes at a random baseline level) but outstripped MaxP by as much 13-28\% after finetuning.

209
04 Jul 2022