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Found 11 papers, 4 papers with code
Bringing Back the Context: Camera Trap Species Identification as Link Prediction on Multimodal Knowledge Graphs
In this work, we leverage the structured context associated with the camera trap images to improve out-of-distribution generalization for the task of species identification in camera traps.
Diversifying Joint Vision-Language Tokenization Learning
Building joint representations across images and text is an essential step for tasks such as Visual Question Answering and Video Question Answering.
A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
To address the limitations of existing KG link prediction frameworks, we propose a novel retrieve-and-read framework, which first retrieves a relevant subgraph context for the query and then jointly reasons over the context and the query with a high-capacity reader.
Ranked #2 on
Link Prediction
on FB15k-237
Knowledge Base Question Answering: A Semantic Parsing Perspective
In this survey, we situate KBQA in the broader literature of semantic parsing and give a comprehensive account of how existing KBQA approaches attempt to address the unique challenges.
A Systematic Investigation of KB-Text Embedding Alignment at Scale
Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support long range reasoning, while text stores more comprehensive and timely knowledge in an unstructured way.
Learning Sparse Mixture of Experts for Visual Question Answering
We aim to tackle this issue for the specific task of Visual Question Answering (VQA).
Structure Learning for Neural Module Networks
In current formulations of such networks only the parameters of the neural modules and/or the order of their execution is learned.
Memory Augmented Self-Play
Self-play is an unsupervised training procedure which enables the reinforcement learning agents to explore the environment without requiring any external rewards.
Reproducibility Report for "Learning To Count Objects In Natural Images For Visual Question Answering"
This is the reproducibility report for the paper "Learning To Count Objects In Natural Images For Visual QuestionAnswering"
Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
Further, unlike existing large scale QA datasets which contain simple questions that can be answered from a single tuple, the questions in our dialogs require a larger subgraph of the KG.
Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks
The stream of words produced by Automatic Speech Recognition (ASR) systems is typically devoid of punctuations and formatting.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
