Papers by Fangping Lan
Making Revisions Understandable: A Survey of Edit Intentions, Methods, and Applications (2026.findings-acl)
Copied to clipboard
| Challenge: | Text revision is a core process in document creation, capturing how authors iteratively refine, reorganize, and improve written content. |
| Approach: | They synthesize text revision research through the lens of edit intentions . they review prior work across the revision workflow including corpus construction, edit intention taxonomies, edit intentions, and edit intention identification. |
| Outcome: | The proposed approach synthesizes datasets, taxonomies, identification methods, and applications and highlights key open research directions. |
Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing studies on ICL for Named Entity Recognition (NER) have mainly explored few-shot settings, but the potential of scaling to hundreds of demonstrations has not been thoroughly investigated. |
| Approach: | They evaluate various LLMs across multiple domains using hundreds of ICL examples and then assess the feasibility of using many-shot ICL as a data annotation framework. |
| Outcome: | The proposed framework can be scaled to hundreds of examples and annotate and refining data for low-resource NER tasks. |
UniT: One Document, Many Revisions, Too Many Edit Intention Taxonomies (2025.findings-acl)
Copied to clipboard
| Challenge: | Current research on edit intentions lacks a comprehensive edit intention taxonomy (EIT) that spans multiple application domains. |
| Approach: | They propose a Unified edit intention taxonomy that integrates existing edit intentions and integrates them into a comprehensive edit intention Taxonomic. |
| Outcome: | The proposed taxonomy achieves higher inter-annotator agreement scores compared to existing taxonomies and is applicable to a large set of application domains. |