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Found 12 papers, 3 papers with code
A Visually-grounded First-person Dialogue Dataset with Verbal and Non-verbal Responses
The results demonstrate that first-person vision helps neural network models correctly understand human intentions, and the production of non-verbal responses is a challenging task like that of verbal responses.
How do people talk about images? A study on open-domain conversations with images.
This paper explores how humans conduct conversations with images by investigating an open-domain image conversation dataset, ImageChat.
RNSum: A Large-Scale Dataset for Automatic Release Note Generation via Commit Logs Summarization
A release note is a technical document that describes the latest changes to a software product and is crucial in open source software development.
A Challenging Multimodal Video Summary: Simultaneously Extracting and Generating Keyframe-Caption Pairs from Video
This paper proposes a practical multimodal video summarization task setting and a dataset to train and evaluate the task.
Off-Policy Evaluation of Ranking Policies under Diverse User Behavior
We show that the resulting estimator, which we call Adaptive IPS (AIPS), can be unbiased under any complex user behavior.
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
We show that the proposed estimator is unbiased in more cases compared to existing estimators that make stronger assumptions.
Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances
With the widespread use of intelligent systems, such as smart speakers, addressee recognition has become a concern in human-computer interaction, as more and more people expect such systems to understand complicated social scenes, including those outdoors, in cafeterias, and hospitals.
Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps
The proposed method is based on a popular VQA method that uses an attention mechanism.
Pretraining Sentiment Classifiers with Unlabeled Dialog Data
Recent studies showed that pretraining with unlabeled data via a language model can improve the performance of classification models.
Cross-domain Recommendation via Deep Domain Adaptation
The behavior of users in certain services could be a clue that can be used to infer their preferences and may be used to make recommendations for other services they have never used.
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning
We investigate the statistical performance and computational efficiency of the alternating minimization procedure for nonparametric tensor learning.
