Moontae Lee

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 73

Top Topics

Incremental Learning

Graph Representation

Diffusion Models

Top Venues

Publications

Takyoung Kim, Kyungjae Lee, Young Rok Jang, Ji Yong Cho, Gangwoo Kim, Minseok Cho, Moontae Lee
Learning to Explore and Select for Coverage-Conditioned Retrieval-Augmented Generation. CoRR (2024)
Hyunseung Lim, Ji Yong Cho, Taewan Kim, Jeongeon Park, Hyungyu Shin, Seulgi Choi, Sunghyun Park, Kyungjae Lee, Juho Kim, Moontae Lee, Hwajung Hong
Co-Creating Question-and-Answer Style Articles with Large Language Models for Research Promotion. Conference on Designing Interactive Systems (2024)
Saelyne Yang, Sunghyun Park, Yunseok Jang, Moontae Lee
YTCommentQA: Video Question Answerability in Instructional Videos. CoRR (2024)
Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Yuchen Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models. CoRR (2024)
Kyungjae Lee, Dasol Hwang, Sunghyun Park, Youngsoo Jang, Moontae Lee
Reinforcement Learning from Reflective Feedback (RLRF): Aligning and Improving LLMs via Fine-Grained Self-Reflection. CoRR (2024)
Seungone Kim, Juyoung Suk, Ji Yong Cho, Shayne Longpre, Chaeeun Kim, Dongkeun Yoon, Guijin Son, Yejin Choi, Sheikh Shafayat, Jinheon Baek, Sue Hyun Park, Hyeonbin Hwang, Jinkyung Jo, Hyowon Cho, Haebin Shin, Seongyun Lee, Hanseok Oh, Noah Lee, Namgyu Ho, Se June Joo, Miyoung Ko, Yoonjoo Lee, Hyungjoo Chae, Jamin Shin, Joel Jang, Seonghyeon Ye, Bill Yuchen Lin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models. CoRR (2024)
Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense. CoRR (2024)
Bangzhao Shu, Lechen Zhang, Minje Choi, Lavinia Dunagan, Lajanugen Logeswaran, Moontae Lee, Dallas Card, David Jurgens
You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments. NAACL-HLT (2024)
Saelyne Yang, Sunghyun Park, Yunseok Jang, Moontae Lee
YTCommentQA: Video Question Answerability in Instructional Videos. AAAI (2024)
Yongrae Jo, Seongyun Lee, Minju Seo, Sung Ju Hwang, Moontae Lee
LG AI Research & KAIST at EHRSQL 2024: Self-Training Large Language Models with Pseudo-Labeled Unanswerable Questions for a Reliable Text-to-SQL System on EHRs. CoRR (2024)
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
Code Models are Zero-shot Precondition Reasoners. NAACL-HLT (2024)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
Small Language Models Need Strong Verifiers to Self-Correct Reasoning. CoRR (2024)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
Small Language Models Need Strong Verifiers to Self-Correct Reasoning. ACL (Findings) (2024)
Sangwoo Shin, Seunghyun Kim, Youngsoo Jang, Moontae Lee, Honguk Woo
Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environments. ACL (Findings) (2024)
Seungyeon Rhyu, Kichang Yang, Sungjun Cho, Jaehyeon Kim, Kyogu Lee, Moontae Lee
Practical and Reproducible Symbolic Music Generation by Large Language Models with Structural Embeddings. CoRR (2024)
Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense. NAACL-HLT (2024)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI (2024)
Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning. CoRR (2023)
Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. CoRR (2023)
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters. AAAI (2023)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Merging Generated and Retrieved Knowledge for Open-Domain QA. CoRR (2023)
Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. CoRR (2023)
Joel Jang, Seungone Kim, Seonghyeon Ye, Doyoung Kim, Lajanugen Logeswaran, Moontae Lee, Kyungjae Lee, Minjoon Seo
Exploring the Benefits of Training Expert Language Models over Instruction Tuning. CoRR (2023)
Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee
Unsupervised Task Graph Generation from Instructional Video Transcripts. CoRR (2023)
Yoonjoo Lee, Kyungjae Lee, Sunghyun Park, Dasol Hwang, Jaehyeon Kim, Hong-In Lee, Moontae Lee
QASA: Advanced Question Answering on Scientific Articles. ICML (2023)
Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. NeurIPS (2023)
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, Minjoon Seo
Knowledge Unlearning for Mitigating Privacy Risks in Language Models. ACL (1) (2023)
Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee
Unsupervised Task Graph Generation from Instructional Video Transcripts. ACL (Findings) (2023)
Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee
Multimodal Subtask Graph Generation from Instructional Videos. CoRR (2023)
Kyungjae Lee, Sang-eun Han, Seung-won Hwang, Moontae Lee
When to Read Documents or QA History: On Unified and Selective Open-domain QA. CoRR (2023)
Hojae Han, Yu Jin Kim, Byoungjip Kim, Youngwon Lee, Kyungjae Lee, Kyungmin Lee, Moontae Lee, Kyunghoon Bae, Seung-won Hwang
On Sample-Efficient Code Generation. EMNLP (Industry Track) (2023)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Few-shot Reranking for Multi-hop QA via Language Model Prompting. ACL (1) (2023)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
GRACE: Discriminator-Guided Chain-of-Thought Reasoning. EMNLP (Findings) (2023)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR (2023)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Merging Generated and Retrieved Knowledge for Open-Domain QA. EMNLP (2023)
Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning. CoRR (2023)
Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning. EMNLP (2023)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Exploring Demonstration Ensembling for In-context Learning. CoRR (2023)
Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. NeurIPS (2023)
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. CoRR (2023)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Discriminator-Guided Multi-step Reasoning with Language Models. CoRR (2023)
Sungwoo Park, Byoungwoo Park, Moontae Lee, Changhee Lee
Neural Stochastic Differential Games for Time-series Analysis. ICML (2023)
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Zhe Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
Code Models are Zero-shot Precondition Reasoners. CoRR (2023)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon
Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR (2023)
Kyungjae Lee, Sang-eun Han, Seung-won Hwang, Moontae Lee
When to Read Documents or QA History: On Unified and Selective Open-domain QA. ACL (Findings) (2023)
Joel Jang, Seungone Kim, Seonghyeon Ye, Doyoung Kim, Lajanugen Logeswaran, Moontae Lee, Kyungjae Lee, Minjoon Seo
Exploring the Benefits of Training Expert Language Models over Instruction Tuning. ICML (2023)
Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim, Sehui Han, Moontae Lee, Honglak Lee, Yousung Jung
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules. ICML (2022)
Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee
Few-shot Subgoal Planning with Language Models. NAACL-HLT (2022)
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters. CoRR (2022)
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. NeurIPS (2022)
Sangjun Han, Hyeongrae Ihm, Moontae Lee, Woohyung Lim
Symbolic Music Loop Generation with Neural Discrete Representations. ISMIR (2022)
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, Minjoon Seo
Knowledge Unlearning for Mitigating Privacy Risks in Language Models. CoRR (2022)
Sangjun Han, Hyeongrae Ihm, Moontae Lee, Woohyung Lim
Symbolic Music Loop Generation with Neural Discrete Representations. CoRR (2022)
Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
Pure Transformers are Powerful Graph Learners. CoRR (2022)
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. CoRR (2022)
Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. NeurIPS (2022)
Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
Is Continual Learning Truly Learning Representations Continually? CoRR (2022)
Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee
CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition. NeurIPS (2022)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA. CoRR (2022)
Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee
Few-shot Subgoal Planning with Language Models. CoRR (2022)
Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR (2022)
Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
Pure Transformers are Powerful Graph Learners. NeurIPS (2022)
Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel
On-the-Fly Rectification for Robust Large-Vocabulary Topic Inference. CoRR (2021)
Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel
On-the-fly Rectification for Robust Large-Vocabulary Topic Inference. ICML (2021)
Moontae Lee, David Bindel, David Mimno
Prior-aware Composition Inference for Spectral Topic Models. AISTATS (2020)
Moontae Lee, Sungjun Cho, David Bindel, David Mimno
Practical Correlated Topic Modeling and Analysis via the Rectified Anchor Word Algorithm. EMNLP/IJCNLP (1) (2019)
Moontae Lee, David M. Mimno
Low-dimensional Embeddings for Interpretable Anchor-based Topic Inference. CoRR (2017)
Moontae Lee, David Bindel, David M. Mimno
Prior-aware Dual Decomposition: Document-specific Topic Inference for Spectral Topic Models. CoRR (2017)
Moontae Lee, David Bindel, David M. Mimno
Robust Spectral Inference for Joint Stochastic Matrix Factorization. CoRR (2016)
Moontae Lee, Seok Hyun Jin, David M. Mimno
Beyond Exchangeability: The Chinese Voting Process. CoRR (2016)
Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng, Paul Smolensky
Reasoning in Vector Space: An Exploratory Study of Question Answering. ICLR (Poster) (2016)
Paul Smolensky, Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng
Basic Reasoning with Tensor Product Representations. CoRR (2016)
Moontae Lee, Seok Hyun Jin, David M. Mimno
Beyond Exchangeability: The Chinese Voting Process. NIPS (2016)
Moontae Lee, David Bindel, David M. Mimno
Robust Spectral Inference for Joint Stochastic Matrix Factorization. NIPS (2015)
David M. Mimno, Moontae Lee
Low-dimensional Embeddings for Interpretable Anchor-based Topic Inference. EMNLP (2014)
Armand Prieditis, Moontae Lee
When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency. MLDM (2013)
Nicolas Kokkalis, Thomas Köhn, Johannes Huebner, Moontae Lee, Florian Schulze, Scott R. Klemmer
TaskGenies: Automatically Providing Action Plans Helps People Complete Tasks. ACM Trans. Comput. Hum. Interact. 20 (5) (2013)
Nicolas Kokkalis, Johannes Huebner, Steven Diamond, Dominic Becker, Michael Chang, Moontae Lee, Florian Schulze, Thomas Köhn, Scott R. Klemmer
Automatically Providing Action Plans Helps People Complete Tasks. HCOMP@AAAI (2012)