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University of Illinois Urbana-Champaign

Event-based knowledge editing for deterministic knowledge propagation in large language models

Abstract

dc:description

The dynamic nature of real-world information necessitates knowledge editing (KE) in large language models (LLMs). This edited knowledge should propagate and facilitate the deduction of new information based on existing model knowledge. We define the existing related knowledge in a LLM serving as the origination of knowledge propagation as ``deduction anchors''. However, most of current KE approaches only operate on (subject, relation, object) triples. Both theoretically and empirically, we observe that this simplified setting often leads to uncertainty when determining the deduction anchors, causing low confidence in their responses. To mitigate this issue, we propose a novel task of event-based knowledge editing that pairs facts with event descriptions. This task manifests both as a closer simulation of real-world editing scenarios and a more logically sound setting, implicitly defining the deduction anchor and enabling LLMs to propagate knowledge confidently. We curate a new benchmark dataset evedit derived from the CounterFact dataset and validate its superiority in improving model confidence. Moreover, as we observe that the event-based setting is notably challenging for existing approaches, we propose a novel approach Self-Edit that showcases stronger performance, achieving 55.6\% consistency improvement while maintaining the naturalness of generation.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois Urbana-Champaign
Year dc:date
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Liu, Jiateng
Contributors dc:contributor
  • Ji, Heng

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • Copyright 2025 Jiateng Liu
Language dc:language
en, eng

Identifiers

dc:identifier.*
Handle dc:identifier
https://hdl.handle.net/2142/129215

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Liu, Jiateng. Event-based knowledge editing for deterministic knowledge propagation in large language models. Thesis thesis, University of Illinois Urbana-Champaign, 2025. https://hdl.handle.net/2142/129215