News Articles

Ambiguity is very high for location names. For example, there are 23 cities named ‘Buffalo’ in the U.S. Based on our previous work, this paper presents a refined hybrid approach …...

In this paper we describe a way to discover Named Entities by using the distribution of words in news articles. Named Entity recog- nition is an important task for today’s …...

Media reporting shapes public opinion which can in turn influence events, partic- ularly in political elections, in which can- didates both respond to and shape public perception of their campaigns. …...

AbstractThis paper describes a rule-based approach to segment Arabic texts into clauses. Our method relies on an extensive analysis of a large set of lexical cues as well as punctuation …...

Recent exploratory efforts in discourse-level language modeling have relied heavily on cal- culating Pointwise Mutual Information (PMI), which involves significant computation when done over large collections. Prior work has required …...

Storyline detection from news articles aims at summarizing events described un- der a certain news topic and revealing how those events evolve over time. It is a dif- ficult task …...

We present an unsupervised model for the discovery and clustering of latent “personas” (characterizations of entities). Our model simultaneously clusters documents featuring similar collections of personas. We evalu- ate this …...

The timeline generation task summarises an entity’s biography by selecting stories representing key events from a large pool of relevant documents. This paper ad- dresses the lack of a standard …...

The problem of noisy and unbalanced train- ing data for supervised keyphrase extraction results from the subjectivity of keyphrase as- signment, which we quantify by crowdsourc- ing keyphrases for news …...

AbstractReal-time summarization of news events (RTS) allows persons to stay up-to-date on important topics that develop over time. With the occurrence of major sub-events, media attention increases and a large …...

AbstractDetecting changes within an unfolding event in real time from news articles or social media enables to react promptly to serious issues in public safety, public health or natural disasters. …...

AbstractThis paper applies BERT to ad hoc document retrieval on news articles, which requires addressing two challenges: relevance judgments in existing test collections are typically provided only at the document …...

AbstractUnbiased and fair reporting is an integral part of ethical journalism. Yet, political propaganda and one-sided views can be found in the news and can cause distrust in media. Both …...

AbstractIn this paper, we deal with two problems in Japanese-English machine translation of news articles. The first problem is the quality of parallel corpora. Neural machine translation (NMT) systems suffer …...

AbstractAdvances in language modeling architectures and the availability of large text corpora have driven progress in automatic text generation. While this results in models capable of generating coherent texts, it …...

AbstractHuman evaluations are typically considered the gold standard in natural language generation, but as models’ fluency improves, how well can evaluators detect and judge machine-generated text? We run a study …...

AbstractFine-tuning a large language model on downstream tasks has become a commonly adopted process in the Natural Language Processing (NLP) (CITATION). However, such a process, when associated with the current …...

In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news arti- cles. Unlike existing models that utilize tex- tual features (e.g., …...

AbstractWe introduce document retrieval and comment generation tasks for automating horizon scanning. This is an important task in the field of futurology that collects sufficient information for predicting drastic societal …...

AbstractResearchers in the social sciences are often interested in the relationship between text and an outcome of interest, where the goal is to both uncover latent patterns in the text …...

AbstractPropaganda aims to persuade an audience by appealing to emotions and using faulty reasoning, with the purpose of promoting a particular point of view. Similarly, metaphor modifies the semantic frame, …...

AbstractWe describe SemEval-2023 task 3 on Detecting the Category, the Framing, and the Persuasion Techniques in Online News in a Multilingual Setup: the dataset, the task organization process, the evaluation …...

AbstractAutomatic headline generation systems have the potential to assist editors in finding interesting headlines to attract visitors or readers. However, the performance of headline generation systems remains challenging due to …...

AbstractKeyphrase extraction aims at automatically extracting a list of “important” phrases representing the key concepts in a document. Prior approaches for unsupervised keyphrase extraction resorted to heuristic notions of phrase …...