5 citations · 7 across the 10 of their papers we have counts for
11 papers · 1 filter
CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?
Jiefu Ou, William Gantt Walden, Kate Sanders +13
A core part of scientific peer review involves providing expert critiques that directly assess the scientific claims a paper makes. While it is now possible to automatically genera…
Small Models Are (Still) Effective Cross-Domain Argument Extractors
William Gantt, Aaron Steven White
Effective ontology transfer has been a major goal of recent work on event argument extraction (EAE). Two methods in particular -- question answering (QA) and template infilling (TI…
Event-Keyed Summarization
William Gantt, Alexander Martin, Pavlo Kuchmiichuk +1
We introduce event-keyed summarization (EKS), a novel task that marries traditional summarization and document-level event extraction, with the goal of generating a contextualized…
MultiMUC: Multilingual Template Filling on MUC-4
William Gantt, Shabnam Behzad, Hannah YoungEun An +4
We introduce MultiMUC, the first multilingual parallel corpus for template filling, comprising translations of the classic MUC-4 template filling benchmark into five languages: Ara…
FAMuS: Frames Across Multiple Sources
Siddharth Vashishtha, Alexander Martin, William Gantt +2
Understanding event descriptions is a central aspect of language processing, but current approaches focus overwhelmingly on single sentences or documents. Aggregating information a…
A Unified View of Evaluation Metrics for Structured Prediction
Yunmo Chen, William Gantt, Tongfei Chen +2
We present a conceptual framework that unifies a variety of evaluation metrics for different structured prediction tasks (e.g. event and relation extraction, syntactic and semantic…
On Event Individuation for Document-Level Information Extraction
William Gantt, Reno Kriz, Yunmo Chen +2
As information extraction (IE) systems have grown more adept at processing whole documents, the classic task of template filling has seen renewed interest as benchmark for document…
Iterative Document-level Information Extraction via Imitation Learning
Yunmo Chen, William Gantt, Weiwei Gu +3
We present a novel iterative extraction model, IterX, for extracting complex relations, or templates (i.e., N-tuples representing a mapping from named slots to spans of text) withi…
Argument Linking: A Survey and Forecast
William Gantt
Semantic role labeling (SRL) -- identifying the semantic relationships between a predicate and other constituents in the same sentence -- is a well-studied task in natural language…
Decomposing and Recomposing Event Structure
William Gantt, Lelia Glass, Aaron Steven White
We present an event structure classification empirically derived from inferential properties annotated on sentence- and document-level Universal Decompositional Semantics (UDS) gra…
Natural Language Inference with Mixed Effects
William Gantt, Benjamin Kane, Aaron Steven White
There is growing evidence that the prevalence of disagreement in the raw annotations used to construct natural language inference datasets makes the common practice of aggregating…