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    • Which Neurons Matter in IR? Applying Integrated Gradients-based Methods to Understand Cross-Encoders
    • Learning Relational Decomposition of Queries for Question Answering from Tables
    • Towards Effective and Efficient Sparse Neural Information Retrieval
    • What Makes Multimodal In-Context Learning Work?
    • Neural ranking model for generating sparse representations for information retrieval
    • LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization
    • LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization
    • CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval
    • CoSPLADE : Adaptation d'un Modèle Neuronal Basé sur des Représentations Parcimonieuses pour la Recherche d'Information Conversationnelle
    • CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval
    • Les systèmes d’intelligence artificielle pour la génération d’images
    • XpmIR: A Modular Library for Learning to Rank and Neural IR Experiments
    • XPMIR: Une bibliothèque modulaire pour l'apprentissage d'ordonnancement et les expériences de RI neuronale
    • From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective
    • Which Discriminator for Cooperative Text Generation?
    • Generative Cooperative Networks for Natural Language Generation
    • Choisir le bon co-équipier pour la génération coopérative de texte
    • Match your words! A study of lexical matching in neural information retrieval
    • IRnator: A Framework for Discovering Users Needs from Sets of Suggestions
    • MLIA-DAC@TREC CAsT 2022: Sparse Contextualized Query Embedding
    • On the Study of Transformers for Query Suggestion
    • Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
    • QuestEval: Summarization Asks for Fact-based Evaluation
    • Skim-Attention: Learning to Focus via Document Layout
    • SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval
    • Skim-Attention: Learning to Focus via Document Layout
    • SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
    • SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
    • To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
    • To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
    • Data-QuestEval: A Referenceless Metric for Data to Text Semantic Evaluation
    • Une Analyse du Modèle ColBERT
    • QuestEval: Summarization Asks for Fact-based Evaluation
    • A White Box Analysis of ColBERT
    • A White Box Analysis of ColBERT
    • Learning Representation for Information Access
    • Discriminative Adversarial Search for Abstractive Summarization
    • Experimaestro and Datamaestro: Experiment and Dataset Managers (for IR)
    • ColdGANs: Taming Language GANs with Cautious Sampling Strategies
    • MLSUM: The Multilingual Summarization Corpus
    • ColdGANs: Taming Language GANs with Cautious Sampling Strategies
    • Using BERT and BART for Query Suggestion
    • Self-Attention Architectures for Answer-Agnostic Neural Question Generation
    • Unsupervised Information Extraction: Regularizing Discriminative Approaches with Relation Distribution Losses
    • Context-Aware Zero-Shot Learning for Object Recognition
    • Un modèle multimodal d’apprentissage de représentations de phrases qui préserve la sémantique visuelle
    • Answers Unite! Unsupervised Metrics for Reinforced Summarization Models
    • Architecture basée sur les mécanismes d'attention: le cas de la génération de questions neuronales
    • Incorporating Visual Semantics into Sentence Representations within a Grounded Space
    • Representation Learning for Classification in Heterogeneous Graphs with Application to Social Networks
    • Apprentissage multimodal de représentation de mots à l'aide de contexte visuel
    • Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification
    • Représentations Gaussiennes pour le Filtrage Collaboratif
    • Learning Multi-Modal Word Representation Grounded in Visual Context
    • Gaussian Embeddings for Collaborative Filtering
    • LIP6@CLEF2017: Multi-Modal Spatial Role Labeling using Word Embeddings Working notes
    • Représentation temporelle des mots : application au clustering de micro-blogs.
    • Apprentissage de Modèles de Langue Neuronaux pour la Recherche d'Information
    • Efficient Document Indexing Using Pivot Tree
    • Learning Term Weights for Ad-hoc Retrieval
    • Modeling Relational Time Series using Gaussian Embeddings
    • Modeling Relational Time Series using Gaussian Embeddings
    • Multilabel Classification on Heterogeneous Graphs with Gaussian Embeddings
    • Graph Based Method Approach to the ImageCLEF2015 Task1 - Image Annotation
    • Inférence de liens signés dans les réseaux sociaux, par apprentissage à partir d'interactions utilisateur
    • Leveraging rating behavior to predict negative social ties
    • Parameterized Neural Network Language Models for Information Retrieval
    • Polarité des jugements et des interactions pour le filtrage collaboratif et la prédiction de liens sociaux.
    • Filtrage collaboratif et intégration de la polarité des notes
    • A comparison of static index pruning methods with temporal queries
    • Diversification Based Static Index Pruning - Application to Temporal Collections
    • Méthodologie pour une représentation multi-dimensionnelle des documents
    • Model Based Comparison of Discounted Cumulative Gain and Average Precision
    • Beyond Cumulated Gain and Average Precision: Including Willingness and Expectation in the User Model
    • On using a quantum physics formalism for multidocument summarization
    • The Kernel Quantum Probabilities (KQP) Library
    • Processing Queries in Session in a Quantum-inspired IR Framework
    • A Query Algebra for Quantum Information Retrieval
    • Handling Data Sparsity in Collaborative Filtering using Emotion and Semantic Based Features
    • Introducción a la recuperación de información
    • On the use of Complex Numbers in Quantum Models for Information Retrieval.
    • Towards a science of user engagement (Position Paper)
    • Supporting Polyrepresentation in a Quantum-inspired Geometrical Retrieval Framework
    • A User Behavior Model for Average Precision and its Generalization to Graded Judgments
    • Dynamics of Genre and Domain Intents
    • Exploring a Multidimensional Representation of Documents and Queries
    • Exploring a Multidimensional Representation of Documents and Queries (extended version)
    • Filtering documents with subspaces
    • What can Quantum Theory bring to IR?
    • Mining User Web Search Activity with Layered Bayesian Networks or How to Capture a Click in its Context
    • A Quantum-based Model for Interactive Information Retrieval
    • A Quantum-based Model for Interactive Information Retrieval (extended version)
    • Evaluation Metrics for Structured Text Retrieval
    • Introduction to the special issue on Graphical Models and Information Retrieval
    • Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering Lecture Notes in Computer Science
    • Sound and Complete Relevance Assessments for XML Retrieval
    • Specificity
    • Structured Information Retrieval and Quantum Theory
    • System and Method for Creating and Applying Predictive User Click Models to Predict a Target Page Associated with a Search Query
    • System and method for deducing user interaction patterns based on limited activities
    • A user browsing model to predict search engine click data from past observations
    • An Extension of Precision-Recall with User Modelling (PRUM): Application to XML Retrieval
    • Effort Precision and Gain-recall based on a probabilistic navigation model
    • Enhancing Educational-Material Retrieval using Authored-Lesson Metadata
    • Predictive User Click Models Based on Click-through History
    • Taking advantage of the semantics of a lesson graph based on learning objects
    • Web Search Engine Evaluation using Clickthrough Data and a User Model
    • A Statistical Model of Query Log Generation
    • Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis
    • Evaluation in (XML) Information Retrieval: Expected Precision-Recall with User Modelling (EPRUM)
    • Principal Components for Automatic Term Hierarchy Building
    • A Bayesian Network for XML Information Retrieval: Searching and Learning with the INEX Collection
    • An algebra for probabilistic XML Retrieval
    • Filtering in XML Retrieval: a Prospective Analysis
    • Interface pour l'évaluation de systèmes de recherche sur des documents XML
    • Providing Consistent and Exhaustive Relevance Assessments for XML Retrieval Evaluation
    • A Machine Learning Model for Information Retrieval with Structured Documents
    • Bayesian Networks and INEX'03
    • Expected Ratio of Relevant Units: A Measure for Structured Information Retrieval
    • INEX Guidelines for Topic Development
    • Structure, recherche d'information et apprentissage
    • Techniques d'apprentissage pour le traitement d'informations structurées : application à la recherche d'information
    • Working group report: the Assessment Tool
    • A Bayesian Network Model for Page Retrieval in a Hierarchically Structured Collection
    • Bayesian networks and INEX
    • Un modèle pour la recherche d'information sur des documents structurés
    • Apprentissage et Recherche Documentaire : une Approche Probabiliste Différentielle
    • Learning in Information Retrieval: a Probabilistic Differential Approach
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Answers Unite! Unsupervised Metrics for Reinforced Summarization Models

Jan 1, 2019·
Thomas Scialom
,
Sylvain Lamprier
,
Benjamin Piwowarski
,
Jacopo Staiano
· 0 min read
Cite DOI
Type
Conference paper
Publication
EMNLP
Last updated on Aug 26, 2024
← Un modèle multimodal d’apprentissage de représentations de phrases qui préserve la sémantique visuelle Mar 1, 2019
Architecture basée sur les mécanismes d'attention: le cas de la génération de questions neuronales Jan 1, 2019 →

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