Embodied agents have achieved prominent performance in following human instructions to
complete tasks. However, the potential of providing instructions informed by texts and …

In this paper, we introduce a novel BERT-enhanced Relational Sentence Ordering Network
(referred to as BRSON) by leveraging BERT for capturing better dependency relationship …

The ability to sequence unordered events is an essential skill to comprehend and reason
about real world task procedures, which often requires thorough understanding of temporal …

Cross-modal coherence modeling is essential for intelligent systems to help them organize
and structure information, thereby understanding and creating content of the physical world …

Dominant sentence ordering models can be classified into pairwise ordering models and set-
to-sequence models. However, there is little attempt to combine these two types of models …

The sentence ordering task aims to organize complex, unordered sentences into readable
text. This improves accuracy, validity, and reliability in various natural language processing …

The massive amounts of data on social media networks can be overwhelming for users; for
this reason, recommending relevant content becomes an essential task to avoid information …

Existing sentence ordering approaches generally employ encoder-decoder frameworks with
the pointer net to recover the coherence by recurrently predicting each sentence step-by …

The task of organizing a shuffled set of sentences into a coherent text has been used to
evaluate a machine's understanding of causal and temporal relations. We formulate the …

Positional reasoning is the process of ordering an unsorted set of parts into a consistent
structure. To address this problem, we present Positional Diffusion, a plug-and-play graph …