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Document Ranking

14 papers with code ยท Natural Language Processing

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TU Wien @ TREC Deep Learning '19 -- Simple Contextualization for Re-ranking

3 Dec 2019

The usage of neural network models puts multiple objectives in conflict with each other: Ideally we would like to create a neural model that is effective, efficient, and interpretable at the same time.

DOCUMENT RANKING WORD EMBEDDINGS

XLNet: Generalized Autoregressive Pretraining for Language Understanding

NeurIPS 2019

With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.

DENOISING DOCUMENT RANKING LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SENTIMENT ANALYSIS

HARE: a Flexible Highlighting Annotator for Ranking and Exploration

IJCNLP 2019

Exploration and analysis of potential data sources is a significant challenge in the application of NLP techniques to novel information domains.

DOCUMENT RANKING

Multi-Stage Document Ranking with BERT

31 Oct 2019

The advent of deep neural networks pre-trained via language modeling tasks has spurred a number of successful applications in natural language processing.

DOCUMENT RANKING LANGUAGE MODELLING

MarlRank: Multi-agent Reinforced Learning to Rank

15 Sep 2019

By defining reward as a function of NDCG, we can optimize our model directly on the ranking performance measure.

DOCUMENT RANKING LEARNING-TO-RANK

A review on ranking problems in statistical learning

6 Sep 2019

We discuss the difficulties when trying to optimize those criteria.

DOCUMENT RANKING FRAUD DETECTION

A Passage-Based Approach to Learning to Rank Documents

5 Jun 2019

Specifically, we devise a suite of learning-to-rank-based document retrieval methods that utilize an effective ranking of passages produced in response to the query; the passage ranking is also induced using a learning-to-rank approach.

DOCUMENT RANKING LEARNING-TO-RANK

Unsupervised Neural Generative Semantic Hashing

3 Jun 2019

We present a novel unsupervised generative semantic hashing approach, \textit{Ranking based Semantic Hashing} (RBSH) that consists of both a variational and a ranking based component.

CODE GENERATION DOCUMENT RANKING INFORMATION RETRIEVAL

Learning Neural Representation for CLIR with Adversarial Framework

EMNLP 2018

In this paper, we follow the success of neural representation in natural language processing (NLP) and develop a novel text representation model based on adversarial learning, which seeks a task-specific embedding space for CLIR.

DOCUMENT RANKING INFORMATION RETRIEVAL MACHINE TRANSLATION REPRESENTATION LEARNING

Repeatability Corner Cases in Document Ranking: The Impact of Score Ties

16 Jul 2018

Due to multi-threaded indexing, which makes experimentation with large modern document collections practical, internal document ids are not assigned consistently between different index instances of the same collection, and thus score ties are broken unpredictably.

DOCUMENT RANKING