activity
20202025
most citedNatural Language Inference with Mixed Effects

5 citations · 7 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2025

WikiVideo: Article Generation from Multiple Videos

Alexander Martin, Reno Kriz, William Gantt Walden +5

We introduce the task of grounded article generation with the goal of creating a Wikipedia-style article from multiple diverse videos about real-world events -- from natural disast…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2023

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…

cs.CL2023

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…

cs.CL2022★ 1 cited

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…

cs.CL2022

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…

cs.CL2021★ 1 cited

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…

cs.CL2021

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…

cs.CL2020★ 5 cited

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…