Yekyung Kim

Hi! I am a second year PhD student at University of Maryland, CLIP Lab advised by Mohit Iyyer with a research focus on natural language processing. I initially started my PhD at UMass NLP and later transferred to UMD along with my advisor.

Before starting PhD, I worked at Hyundai Motors Group and LG Electronics as a research engineer. I was fortunate to be selected as a specialist in AI and researched at CMU LTI as a visiting scientist mentored by Jaime Carbonell.

Email / Google Scholar / Github

Research

My research focuses on evaluating and improving language models, particularly in long-context scenarios. More specifically, my current research focuses on:

• How faithfully LLM generate content from long inputs, and how to verify it

• Understanding and optimizing the impact of data on long-context reasoning

	One ruler to measure them all: Benchmarking multilingual long-context language models Yekyung Kim, Jenna Russell, Marzena Karpinska, Mohit Iyyer arXiv 2025 Code
	VERISCORE: Evaluating the Factuality of Verifiable Claims in Long-form Text Generation Yixiao Song, Yekyung Kim, Mohit Iyyer Accepted by EMNLP Findings 2024 Code
	FABLES: Evaluating Faithfulness and Content Selection in Book-length Summarization Yekyung Kim, Yapei Chang, Marzena Karpinska, Aparna Garimella, Varun Manjunatha, Kyle Lo, Tanya Goyal, Mohit Iyyer COLM 2024 Dataset + Code
	Is it safe to cross? Interpretable Risk Assessment with GPT-4V for Safety-Aware Street Crossing Hochul Hwang, Sunjae Kwon, Yekyung Kim, 21st International Conference on Ubiquitous Robots
	LINDA: Unsupervised Learning to Interpolate in Natural Language Processing Yekyung Kim, Seohyeong Jeong, Kyunghyun Cho arXiv
	A Universal Framework for Dataset Characterization with Multidimensional Meta-information Jaehyung Kim Yekyung Kim, Karin Johanna Denton de Langis, Jinwoo Shin, Dongyeop Kang ACL 2023 code
	Meta-Crafting: Improved Detection of Out-of-distributed Texts via Crafting Metadata Space Ryan Koo, Yekyung Kim, Dongyeop Kang, Jaehyung Kim AAAI 2024 Student Abstract and Poster Program
	Deep Active Learning for Sequence Labeling Based on Diversity and Uncertainty in Gradient Yekyung Kim Workshop on Life-long Learning for Spoken Language Systems at AACL, 2021
	Learning Sub-Character level representation forKorean Named Entity Recognition Yejin Kim, Yekyung Kim (equal contributions) The International FLAIRS Conference Proceedings , 2020
	#Nowplaying the Future Billboard: Mining Music Listening Behaviors of Twitter Users for Hit Song Prediction Yekyung Kim, Bongwon Suh, Kyogu Lee Workshop on Social Media Retrieval and Analysis (SoMeRA) at SIGIR , 2014
	A Visual Analytics Approach to Summarizing Tweets Ramik Sadana, Yekyung Kim , Bongwon Suh, Eunyee Koh Industry day at SIGIR , 2014

Industry Project

	Airstar - Incheon Airport Robot, LG Electronics
	AI assistant for car, Hyundai
	Chatbot for home-appliances, LG Electronics