1.8k citations · 3.2k across the 64 of their papers we have counts for
7 papers · 1 filter
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation
Xin Dong, Jingchao Ni, Wei Cheng +6
Recently, recommender systems have been able to emit substantially improved recommendations by leveraging user-provided reviews. Existing methods typically merge all reviews of a g…
SCALOR: Generative World Models with Scalable Object Representations
Jindong Jiang, Sepehr Janghorbani, Gerard de Melo +1
Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning. Most of the previous models have been s…
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Yikun Xian, Zuohui Fu, S. Muthukrishnan +2
Recent advances in personalized recommendation have sparked great interest in the exploitation of rich structured information provided by knowledge graphs. Unlike most existing app…
OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization
Bingchen Liu, Yizhe Zhu, Zuohui Fu +2
Exploring the potential of GANs for unsupervised disentanglement learning, this paper proposes a novel GAN-based disentanglement framework with One-Hot Sampling and Orthogonal Regu…
Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts
Rajarshi Bhowmik, Gerard de Melo
Despite being vast repositories of factual information, cross-domain knowledge graphs, such as Wikidata and the Google Knowledge Graph, only sparsely provide short synoptic descrip…
CITE: A Corpus of Image-Text Discourse Relations
Malihe Alikhani, Sreyasi Nag Chowdhury, Gerard de Melo +1
This paper presents a novel crowd-sourced resource for multimodal discourse: our resource characterizes inferences in image-text contexts in the domain of cooking recipes in the fo…
Using Multi-Sense Vector Embeddings for Reverse Dictionaries
Michael A. Hedderich, Andrew Yates, Dietrich Klakow +1
Popular word embedding methods such as word2vec and GloVe assign a single vector representation to each word, even if a word has multiple distinct meanings. Multi-sense embeddings…