Who cites «A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)» · page 2

192 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

État des lieux des Transformers Vision-Langage : Un éclairage sur les données de pré-entraînement — 2023 · Actes de CORIA-TALN 2023. Actes de la 30e Conférence sur le Traitement Automatique des Langues Naturelles (TALN), volume 3 : prises de position en TAL
Abstract Visual Reasoning with Tangram Shapes — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
An Anchor-based Relative Position Embedding Method for Cross-Modal Tasks — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
AnaLog: Testing Analytical and Deductive Logic Learnability in Language Models — 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation — 2022 · arXiv:2201.12086
CoCa: Contrastive Captioners are Image-Text Foundation Models — 2022 · arXiv:2205.01917
Distilled Dual-Encoder Model for Vision-Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
End-to-End Unsupervised Vision-and-Language Pre-training with Referring Expression Matching — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Finding Structural Knowledge in Multimodal-BERT — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Image Retrieval from Contextual Descriptions — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Late Fusion with Triplet Margin Objective for Multimodal Ideology Prediction and Analysis — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Learning to Generate Programs for Table Fact Verification via Structure-Aware Semantic Parsing — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Multilingual Multimodal Learning with Machine Translated Text — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Named Entity and Relation Extraction with Multi-Modal Retrieval — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Probing the Role of Positional Information in Vision-Language Models — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training — 2022 · arXiv:2211.11446
Semantically Distributed Robust Optimization for Vision-and-Language Inference — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
TRIPS: Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Transformer-based Localization from Embodied Dialog with Large-scale Pre-training — 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions — 2022 · Proceedings of the Workshop on Unimodal and Multimodal Induction of Linguistic Structures (UM-IoS)
VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Visual Programming: Compositional visual reasoning without training — 2022 · arXiv:2211.11559
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
xGQA: Cross-Lingual Visual Question Answering — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Building a Video-and-Language Dataset with Human Actions for Multimodal Logical Inference — 2021 · Proceedings of the 1st Workshop on Multimodal Semantic Representations (MMSR)
COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Caption Enriched Samples for Improving Hateful Memes Detection — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Constrained Language Models Yield Few-Shot Semantic Parsers — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Data Efficient Masked Language Modeling for Vision and Language — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy Minimization — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies — 2021
Edited Media Understanding Frames: Reasoning About the Intent and Implications of Visual Misinformation — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Grounding `Grounding' in NLP — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Investigating Negation in Pre-trained Vision-and-language Models — 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Mind the Context: The Impact of Contextualization in Neural Module Networks for Grounding Visual Referring Expressions — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Multi-stage Pre-training over Simplified Multimodal Pre-training Models — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs — 2021 · Transactions of the Association for Computational Linguistics
Probing Cross-Modal Representations in Multi-Step Relational Reasoning — 2021 · Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021)
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge — 2021 · Proceedings of the Third Workshop on Beyond Vision and LANguage: inTEgrating Real-world kNowledge (LANTERN)
SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning — our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables — 2021 · Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision — 2021 · arXiv:2108.10904
TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training — 2021 · Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Transformer-Exclusive Cross-Modal Representation for Vision and Language — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Unsupervised Vision-and-Language Pre-training Without Parallel Images and Captions — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision — 2021 · arXiv:2102.03334
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Volta at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables using TAPAS and Transfer Learning — 2021 · Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Achieving Common Ground in Multi-modal Dialogue — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts
Adjusting Image Attributes of Localized Regions with Low-level Dialogue — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
Be Different to Be Better! A Benchmark to Leverage the Complementarity of Language and Vision — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
Benchmarking Multimodal Regex Synthesis with Complex Structures — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Break It Down: A Question Understanding Benchmark — 2020 · Transactions of the Association for Computational Linguistics
CompGuessWhat?!: A Multi-task Evaluation Framework for Grounded Language Learning — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Cross-Modality Relevance for Reasoning on Language and Vision — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think! — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Evaluating Models' Local Decision Boundaries via Contrast Sets — our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
Experience Grounds Language — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
How Can We Accelerate Progress Towards Human-like Linguistic Generalization? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Learning to Represent Image and Text with Denotation Graph — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
New Protocols and Negative Results for Textual Entailment Data Collection — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Obtaining Faithful Interpretations from Compositional Neural Networks — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks — 2020 · arXiv:2004.06165
Profile Consistency Identification for Open-domain Dialogue Agents — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts
The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes — 2020 · arXiv:2005.04790
Understanding tables with intermediate pre-training — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
VD-BERT: A Unified Vision and Dialog Transformer with BERT — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
What Does BERT with Vision Look At? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
多模态视觉语言表征学习研究综述 — 2020 · 软件学报 (Journal of Software)
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Expressing Visual Relationships via Language — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering — 2019 · arXiv:1902.09506
Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
LXMERT: Learning Cross-Modality Encoder Representations from Transformers — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Neural Naturalist: Generating Fine-Grained Image Comparisons — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
TabFact: A Large-scale Dataset for Table-based Fact Verification — 2019 · arXiv:1909.02164
UNITER: UNiversal Image-TExt Representation Learning — 2019 · arXiv:1909.11740
VisualBERT: A Simple and Performant Baseline for Vision and Language — 2019 · arXiv:1908.03557
Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments — 2018 · arXiv:1811.12354 · Published in CVPR 2019