Large Language Models (LLMs) have taken Knowledge Representation – and t...
Given the success of Graph Neural Networks (GNNs) for structure-aware ma...
Using model weights pretrained on a high-resource language as a warm sta...
Recent breakthroughs in self supervised training have led to a new class...
The recent hype around Reddit's WallStreetBets (WSB) community has inspi...
We introduce ViLPAct, a novel vision-language benchmark for human activi...
Video recognition has been dominated by the end-to-end learning paradigm...
Recently CKY-based models show great potential in unsupervised grammar
i...
Creating meaningful art is often viewed as a uniquely human endeavor. A ...
Contrastive Language–Image Pre-training (CLIP) has shown remarkable succ...
Inspired by the success of BERT, several multimodal representation learn...
Human language understanding operates at multiple levels of granularity
...
Reddit's WallStreetBets (WSB) community has come to prominence in light ...
What do word vector representations reveal about the emotions associated...
Impressive milestones have been achieved in text matching by adopting a
...
Biomedical entity linking is the task of identifying mentions of biomedi...
Coping with ambiguous questions has been a perennial problem in real-wor...
As news and social media exhibit an increasing amount of manipulative
po...
Software development is becoming increasingly open and collaborative wit...
In this work, we present a new dataset for conversational recommendation...
Several multi-modality representation learning approaches such as LXMERT...
Emergentism and pragmatics are two research fields that study the dynami...
There has been growing attention on fairness considerations recently,
es...
Focusing on text-to-image (T2I) generation, we propose Text and Image
Mu...
In this paper, we explore the artificial generation of typographical err...
Given the growing ubiquity of emojis in language, there is a need for me...
Despite their large-scale coverage, existing cross-domain knowledge grap...
While important properties of word vector representations have been stud...
In this paper we provide a comprehensive introduction to knowledge graph...
In the past decade, there has been substantial progress at training
incr...
A number of cross-lingual transfer learning approaches based on neural
n...
Recently, recommender systems have been able to emit substantially impro...
The main limitation of previous approaches to unsupervised sequential
ob...
Recent advances in personalized recommendation have sparked great intere...
Exploring the potential of GANs for unsupervised disentanglement learnin...
Despite being vast repositories of factual information, cross-domain
kno...
This paper presents a novel crowd-sourced resource for multimodal discou...
Popular word embedding methods such as word2vec and GloVe assign a singl...
While large-scale knowledge graphs provide vast amounts of structured fa...
Recently, substantial research effort has focused on how to apply CNNs o...
Neural IR models, such as DRMM and PACRR, have achieved strong results b...
In order to adopt deep learning for information retrieval, models are ne...
Recently, video captioning has been attracting an increasing amount of
i...
Many real-world problems involving constraints can be regarded as instan...