News Discourse Profiling seeks to scrutinize the event-related role of e...
Rhetorical Structure Theory based Discourse Parsing (RST-DP) explores ho...
Vector representations of natural language are ubiquitous in search
appl...
Language models pretrained on large collections of tabular data have
dem...
We propose to leverage news discourse profiling to model document-level
...
Complex feature extractors are widely employed for text representation
b...
Python type inference is challenging in practice. Due to its dynamic
pro...
Event data are prevalent in diverse domains such as financial trading,
b...
We present a new benchmark dataset called PARADE for paraphrase
identifi...
People increasingly use social media to report emergencies, seek help or...
The increasing prevalence of political bias in news media calls for grea...
A typical conversation comprises of multiple turns between participants ...
Capabilities to categorize a clause based on the type of situation entit...
Inspired by the double temporality characteristic of narrative texts, we...
We argue that semantic meanings of a sentence or clause can not be
inter...
In this paper, we describe TAMU's system submitted to the TAC KBP 2017 e...
In the wake of a polarizing election, the cyber world is laden with hate...
In the wake of a polarizing election, social media is laden with hateful...
Focusing on the task of identifying event temporal status, we find that
...
Capabilities of detecting temporal relations between two events can bene...
The lack of large realistic datasets presents a bottleneck in online
dec...
We introduce a novel iterative approach for event coreference resolution...
We present a sequential model for temporal relation classification betwe...