To Eun Kim
Scholar

To Eun Kim

Google Scholar ID: 3ymamHAAAAAJ
Carnegie Mellon University
Natural Language ProcessingInformation RetrievalMachine Learning
Citations & Impact
All-time
Citations
98
 
H-index
5
 
i10-index
4
 
Publications
14
 
Co-authors
19
list available
Resume (English only)
Academic Achievements
  • Published 'MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers' at EMNLP 2025
  • Published 'TeamCMU at Touché: Adversarial Co-Evolution for Advertisement Integration and Detection in Conversational Search' at CLEF 2025 Touché Lab (Best Paper Award)
  • Published 'LTRR: Learning To Rank Retrievers for LLMs' at SIGIR 2025 LiveRAG Workshop
  • Contributed to international evaluation campaigns including TREC and NTCIR, especially the Tip-of-the-Tongue retrieval track
  • Participated in NeurIPS 2022 IGLU Competition on asking clarifying questions
Background
  • Third-year PhD student at the Language Technologies Institute (LTI), Carnegie Mellon University
  • Research focuses on retrieval-enhanced machine learning (REML) and retrieval-augmented generation (RAG)
  • Addresses real-world AI system challenges such as data provider attribution and advertisement strategies in conversational search
  • Works on evaluation and benchmarking of AI systems, including user and query simulators
  • Aims to make AI systems more efficient, reliable, and responsible in real-world settings