← Learning Types
Deep Learning › Learning Types ›

Multimodal Learning

323 directly classified papers

Papers per year

Papers

Exploiting Commonsense Knowledge about Objects for Visual Activity Recognition ACL 2023
Putting Natural in Natural Language Processing ACL 2023
Stereotypes and Smut: The (Mis)representation of Non-cisgender Identities by Text-to-Image Models ACL 2023
RC3: Regularized Contrastive Cross-lingual Cross-modal Pre-training ACL 2023
UnLoc: A Unified Framework for Video Localization Tasks ICCV 2023
Multimodal Industrial Anomaly Detection via Hybrid Fusion CVPR 2023
Long-Term Rhythmic Video Soundtracker ICML 2023
GenKIE: Robust Generative Multimodal Document Key Information Extraction EMNLP 2023
MAGVLT: Masked Generative Vision-and-Language Transformer CVPR 2023
Beneath the Surface: Unveiling Harmful Memes with Multimodal Reasoning Distilled from Large Language Models EMNLP 2023
Token Mixing: Parameter-Efficient Transfer Learning from Image-Language to Video-Language AAAI 2023
Sentiment Knowledge Enhanced Self-supervised Learning for Multimodal Sentiment Analysis ACL 2023
MNER-QG: An End-to-End MRC Framework for Multimodal Named Entity Recognition with Query Grounding AAAI 2023
Mutual-Enhanced Incongruity Learning Network for Multi-Modal Sarcasm Detection AAAI 2023
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis ACL 2023
What Do You MEME? Generating Explanations for Visual Semantic Role Labelling in Memes AAAI 2023
SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions NIPS 2023
Towards Unified, Explainable, and Robust Multisensory Perception AAAI 2023
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation NIPS 2023
Mass-Producing Failures of Multimodal Systems with Language Models NIPS 2023
Grounding Answers for Visual Questions Asked by Visually Impaired People CVPR 2022
Visual Emotion Representation Learning via Emotion-Aware Pre-training IJCAI 2022
Are Vision-Language Transformers Learning Multimodal Representations? A Probing Perspective AAAI 2022
How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions? EMNLP 2022
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective EMNLP 2022