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To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs

We propose a new training framework for Language GANs based on cooperative decoding search and self-training.

QuestEval: Summarization Asks for Fact-based Evaluation

Summarization evaluation remains an open research problem: current metrics such as ROUGE are known to be limited and to correlate poorly with human judgments. To alleviate this issue, recent work has proposed evaluation metrics which rely on question …

SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking

In neural Information Retrieval, ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using efficient approximate nearest neighbors methods has proven to work well. …

Une Analyse du Modèle ColBERT

Les modèles de RI basés sur les Transformers sont aujourd’hui état de l’art en Recherche d’Information ad-hoc, mais leur comportement reste encore incompris. Des travaux récents ont montré que BERT ne satisfait pas les axiomes classiques de la RI. …

A White Box Analysis of ColBERT

Transformer-based models are nowadays state-of-the-art in adhoc Information Retrieval, but their behavior are far from being understood. Recent work has claimed that BERT does not satisfy the classical IR axioms. However, we propose to dissect the …

Modeling Relational Time Series using Gaussian Embeddings

We address the problem of modeling multiple simultaneous time series where the observations are correlated not only inside each series, but among the different series. This problem happens in many domains such as ecology, meteorology, etc. We propose …

Using BERT and BART for Query Suggestion

Transformer networks have recently been successfully applied on a very large range of NLP tasks. Surprisingly, they have never been employed for query suggestion, although their sequence-tosequence architecture makes them particularly appealing for …

Discriminative Adversarial Search for Abstractive Summarization

We introduce a novel approach for sequence decoding, Discriminative Adversarial Search (DAS), which has the desirable properties of alleviating the effects of exposure bias without requiring external metrics. Inspired by Generative Adversarial …

Experimaestro and Datamaestro: Experiment and Dataset Managers (for IR)

Incorporating Visual Semantics into Sentence Representations within a Grounded Space