Search Results for author:
Found 12 papers, 8 papers with code
ULTRA: Unleash LLMs' Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Refinement
Event argument extraction (EAE), at the core of event-centric understanding, is the task of identifying role-specific text spans (i. e., arguments) for a given event.
MOKA: Moral Knowledge Augmentation for Moral Event Extraction
News media employ moral language to create memorable stories, and readers often engage with the content that align with their values.
Crossing the Aisle: Unveiling Partisan and Counter-Partisan Events in News Reporting
We benchmark PAC to highlight the challenges of this task.
All Things Considered: Detecting Partisan Events from News Media with Cross-Article Comparison
Public opinion is shaped by the information news media provide, and that information in turn may be shaped by the ideological preferences of media outlets.
You Are What You Annotate: Towards Better Models through Annotator Representations
Annotator disagreement is ubiquitous in natural language processing (NLP) tasks.
Late Fusion with Triplet Margin Objective for Multimodal Ideology Prediction and Analysis
In this work, we introduce the task of multimodal ideology prediction, where a model predicts binary or five-point scale ideological leanings, given a text-image pair with political content.
Generative Entity-to-Entity Stance Detection with Knowledge Graph Augmentation
We present a novel generative framework to allow the generation of canonical names for entities as well as stances among them.
POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection
Ideology is at the core of political science research.
Towards More Robust Natural Language Understanding
Therefore, in order to have NLU models understand human language more effectively, it is expected to prioritize the study on robust natural language understanding.
Identifying inherent disagreement in natural language inference
Natural language inference (NLI) is the task of determining whether a piece of text is entailed, contradicted by or unrelated to another piece of text.
CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering
Clinical question answering (QA) aims to automatically answer questions from medical professionals based on clinical texts.
COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval
For evaluation, we introduce Query Bank and Relevance Set, where the former contains 1, 236 human-paraphrased queries while the latter contains ~32 human-annotated FAQ items for each query.
