In-context learning (ICL) improves language models' performance on a var...
Although much literature has established the presence of demographic bia...
Despite remarkable advancements in few-shot generalization in natural
la...
Language models (LMs) often struggle to pay enough attention to the inpu...
Despite the major advances in NLP, significant disparities in NLP system...
Empowering language is important in many real-world contexts, from educa...
Large language models (LLMs) are increasingly adopted for a variety of t...
Large language models (LLMs) are increasingly adopted for knowledge-inte...
Large language models (LMs) are pretrained on diverse data sources: news...
Evaluating the factual consistency of automatically generated summaries ...
Large language models can perform new tasks in a zero-shot fashion, give...
Mental health stigma prevents many individuals from receiving the approp...
Abstractive summarization models often generate inconsistent summaries
c...
With the advent of pre-trained language models (LMs), increasing researc...
Large pretrained language models have been performing increasingly well ...
In this report, we describe a new data set called VoynaSlov which contai...
Natural language processing (NLP) models trained on people-generated dat...
Keyphrase extraction aims at automatically extracting a list of "importa...
Online platforms and communities establish their own norms that govern w...
Among the most critical limitations of deep learning NLP models are thei...
Recent work has shown fine-tuning neural coreference models can produce
...
Adapters are light-weight modules that allow parameter-efficient fine-tu...
With recent progress in joint modeling of visual and textual representat...
Despite inextricable ties between race and language, little work has
con...
Open-domain neural dialogue models have achieved high performance in res...
To successfully negotiate a deal, it is not enough to communicate fluent...
Modern summarization models generate highly fluent but often factually
u...
Dense retrieval has been shown to be effective for retrieving relevant
d...
Text generation systems are ubiquitous in natural language processing
ap...
Social biases on Wikipedia, a widely-read global platform, could greatly...
Specific lexical choices in how people are portrayed both reflect the
wr...
Massively multilingual models subsuming tens or even hundreds of languag...
Modern toxic speech detectors are incompetent in recognizing disguised
o...
Modern multilingual models are trained on concatenated text from multipl...
Creating a descriptive grammar of a language is an indispensable step fo...
Dialogue systems pretrained with large language models generate locally
...
In this paper we describe our submission for the task of Propaganda Span...
Cross-lingual transfer learning studies how datasets, annotations, and m...
In current hate speech datasets, there exists a high correlation between...
Between February 14, 2019 and March 4, 2019, a terrorist attack in Pulwa...
Modern deep learning models for NLP are notoriously opaque. This has
mot...
Despite their prevalence in society, social biases are difficult to defi...
When training multilingual machine translation (MT) models that can tran...
Dehumanization is a pernicious psychological process that often leads to...
Traditional preneural approaches to single document summarization relied...
We perform statistical analysis of the phenomenon of neology, the proces...
Negotiation is a complex activity involving strategic reasoning, persuas...
We study non-collaborative dialogs, where two agents have a conflict of
...
Despite impressive performance on many text classification tasks, deep n...
This paper presents the submission by the CMU-01 team to the SIGMORPHON ...