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H. Kim

12 papers hereh-index 6356 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author10

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.HC4
  • cs.AI2
  • cs.DB2
same name
  • H. Kim — 326 papers
  • H. Kim — 298 papers
  • H. Kim — 118 papers, h 62
  • H. Kim — 115 papers, h 41
  • H. Kim — 85 papers, h 0
  • H. Kim — 78 papers, h 65

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedTowards Transparent, Reusable, and Customizable Data Science in Computational Notebooks

5 citations · 13 across the 12 of their papers we have counts for

collaborators
Showing cs.HCShow all

4 papers · 1 filter

cs.HC2025

AIPOM: Agent-aware Interactive Planning for Multi-Agent Systems

Hannah Kim, Kushan Mitra, Chen Shen +2

Large language models (LLMs) are being increasingly used for planning in orchestrated multi-agent systems. However, existing LLM-based approaches often fall short of human expectat…

cs.HC2024

Knowledge Acquisition and Integration with Expert-in-the-loop

Sajjadur Rahman, Frederick Choi, Hannah Kim +2

Constructing and serving knowledge graphs (KGs) is an iterative and human-centered process involving on-demand programming and analysis. In this paper, we present Kyurem, a program…

cs.HC2023★ 5 cited

Towards Transparent, Reusable, and Customizable Data Science in Computational Notebooks

Frederick Choi, Sajjadur Rahman, Hannah Kim +1

Data science workflows are human-centered processes involving on-demand programming and analysis. While programmable and interactive interfaces such as widgets embedded within comp…

cs.HC2023★ 2 cited

MEGAnno: Exploratory Labeling for NLP in Computational Notebooks

Dan Zhang, Hannah Kim, Rafael Li Chen +2

We present MEGAnno, a novel exploratory annotation framework designed for NLP researchers and practitioners. Unlike existing labeling tools that focus on data labeling only, our fr…

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