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Found 25 papers, 8 papers with code
A Monte Carlo Language Model Pipeline for Zero-Shot Sociopolitical Event Extraction
We consider dyadic zero-shot event extraction (EE) to identify actions between pairs of actors.
A Comparative Analysis Of Latent Regressor Losses For Singing Voice Conversion
We propose an alternative loss component in a loss function that is otherwise well-established among VC tasks, which has been shown to improve our model's SVC performance.
Examining Political Rhetoric with Epistemic Stance Detection
Participants in political discourse employ rhetorical strategies -- such as hedging, attributions, or denials -- to display varying degrees of belief commitments to claims proposed by themselves or others.
ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution
Large-scale, high-quality corpora are critical for advancing research in coreference resolution.
Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties
The study of language variation examines how language varies between and within different groups of speakers, shedding light on how we use language to construct identities and how social contexts affect language use.
Text as Causal Mediators: Research Design for Causal Estimates of Differential Treatment of Social Groups via Language Aspects
Using observed language to understand interpersonal interactions is important in high-stakes decision making.
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
Automated event extraction in social science applications often requires corpus-level evaluations: for example, aggregating text predictions across metadata and unbiased estimates of recall.
Analyzing Gender Bias within Narrative Tropes
Popular media reflects and reinforces societal biases through the use of tropes, which are narrative elements, such as archetypal characters and plot arcs, that occur frequently across media.
Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty
We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index.
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates
For example, an individual's entire history of social media posts or the content of a news article could provide a rich measurement of multiple confounders.
Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts
Sports broadcasters inject drama into play-by-play commentary by building team and player narratives through subjective analyses and anecdotes.
Query-focused Sentence Compression in Linear Time
Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface.
Human acceptability judgements for extractive sentence compression
Recent approaches to English-language sentence compression rely on parallel corpora consisting of sentence-compression pairs.
Evaluating Syntactic Properties of Seq2seq Output with a Broad Coverage HPSG: A Case Study on Machine Translation
We explore whether such output belongs to a formal and realistic grammar, by employing the English Resource Grammar (ERG), a broad coverage, linguistically precise HPSG-based grammar of English.
Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
Dependency parsing research, which has made significant gains in recent years, typically focuses on improving the accuracy of single-tree predictions.
Rookie: A unique approach for exploring news archives
News archives are an invaluable primary source for placing current events in historical context.
Identifying civilians killed by police with distantly supervised entity-event extraction
We propose a new, socially-impactful task for natural language processing: from a news corpus, extract names of persons who have been killed by police.
Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English
We highlight an important frontier in algorithmic fairness: disparity in the quality of natural language processing algorithms when applied to language from authors of different social groups.
Demographic Dialectal Variation in Social Media: A Case Study of African-American English
Though dialectal language is increasingly abundant on social media, few resources exist for developing NLP tools to handle such language.
Visualizing textual models with in-text and word-as-pixel highlighting
We explore two techniques which use color to make sense of statistical text models.
Posterior calibration and exploratory analysis for natural language processing models
Many models in natural language processing define probabilistic distributions over linguistic structures.
ARKref: a rule-based coreference resolution system
At the time of writing, the last released version was in March 2011.
Learning Frames from Text with an Unsupervised Latent Variable Model
We develop a probabilistic latent-variable model to discover semantic frames---types of events and their participants---from corpora.
A framework for (under)specifying dependency syntax without overloading annotators
We introduce a framework for lightweight dependency syntax annotation.
Diffusion of Lexical Change in Social Media
Computer-mediated communication is driving fundamental changes in the nature of written language.
