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

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Latest papers with code

Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits

12 Feb 2021oaqa/FlexNeuART

We study the utility of the lexical translation model (IBM Model 1) for English text retrieval, in particular, its neural variants that are trained end-to-end.

DOCUMENT RANKING INFORMATION RETRIEVAL

107
12 Feb 2021

On the Calibration and Uncertainty of Neural Learning to Rank Models

12 Jan 2021Guzpenha/transformer_rankers

Our experimental results on the ad-hoc retrieval task of conversation response ranking reveal that (i) BERT-based rankers are not robustly calibrated and that stochastic BERT-based rankers yield better calibration; and (ii) uncertainty estimation is beneficial for both risk-aware neural ranking, i. e. taking into account the uncertainty when ranking documents, and for predicting unanswerable conversational contexts.

DOCUMENT RANKING LEARNING-TO-RANK

71
12 Jan 2021

Long Document Ranking with Query-Directed Sparse Transformer

23 Oct 2020hallogameboy/QDS-Transformer

In this paper, we design Query-Directed Sparse attention that induces IR-axiomatic structures in transformer self-attention.

DOCUMENT RANKING

11
23 Oct 2020

Longformer for MS MARCO Document Re-ranking Task

20 Sep 2020isekulic/longformer-marco

Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard.

DOCUMENT RANKING INFORMATION RETRIEVAL RE-RANKING

8
20 Sep 2020

Simplified TinyBERT: Knowledge Distillation for Document Retrieval

16 Sep 2020cxa-unique/Simplified-TinyBERT

Despite the effectiveness of utilizing the BERT model for document ranking, the high computational cost of such approaches limits their uses.

DOCUMENT RANKING KNOWLEDGE DISTILLATION

3
16 Sep 2020

Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering

12 Aug 2020sebastian-hofstaetter/fira-trec-19-dataset

We extend the ranked retrieval annotations of the Deep Learning track of TREC 2019 with passage and word level graded relevance annotations for all relevant documents.

DOCUMENT RANKING QUESTION ANSWERING

5
12 Aug 2020

GLOW : Global Weighted Self-Attention Network for Web Search

10 Jul 2020cadobe/bison

Deep matching models aim to facilitate search engines retrieving more relevant documents by mapping queries and documents into semantic vectors in the first-stage retrieval.

DOCUMENT RANKING INFORMATION RETRIEVAL TOKENIZATION WORD EMBEDDINGS

24
10 Jul 2020

Local Self-Attention over Long Text for Efficient Document Retrieval

11 May 2020sebastian-hofstaetter/transformer-kernel-ranking

In this work, we propose a local self-attention which considers a moving window over the document terms and for each term attends only to other terms in the same window.

DOCUMENT RANKING

72
11 May 2020

Efficient Document Re-Ranking for Transformers by Precomputing Term Representations

29 Apr 2020Georgetown-IR-Lab/prettr-neural-ir

Deep pretrained transformer networks are effective at various ranking tasks, such as question answering and ad-hoc document ranking.

DOCUMENT RANKING QUESTION ANSWERING RE-RANKING

4
29 Apr 2020

ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

27 Apr 2020stanford-futuredata/ColBERT

ColBERT introduces a late interaction architecture that independently encodes the query and the document using BERT and then employs a cheap yet powerful interaction step that models their fine-grained similarity.

DOCUMENT RANKING INFORMATION RETRIEVAL NATURAL LANGUAGE UNDERSTANDING RE-RANKING

172
27 Apr 2020