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2020 – today
- 2024
[c46]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- [c45]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI 2024: 11186-11194 - [c44]Saelyne Yang, Sunghyun Park, Yunseok Jang, Moontae Lee:
YTCommentQA: Video Question Answerability in Instructional Videos. AAAI 2024: 19359-19367 - [c43]Sangwoo Shin, Seunghyun Kim, Youngsoo Jang, Moontae Lee, Honguk Woo:
Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environments. ACL (Findings) 2024: 3354-3376 - [c42]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: 15637-15653 - [c41]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. ClinicalNLP@NAACL 2024: 635-643 - [c40]Byoungjip Kim, Dasol Hwang, Sungjun Cho, Youngsoo Jang, Honglak Lee, Moontae Lee:
Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning. CVPR Workshops 2024: 1808-1817 - [c39]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. EMNLP 2024: 4334-4353 - [c38]Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, Moontae Lee:
Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking. EMNLP (Findings) 2024: 14958-14976 - [c37]Mingqian Zheng, Jiaxin Pei, Lajanugen Logeswaran, Moontae Lee, David Jurgens:
When "A Helpful Assistant" Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models. EMNLP (Findings) 2024: 15126-15154 - [c36]Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee, Moontae Lee:
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration. ICML 2024 - [c35]Haeju Park, Kyungjae Lee, Sunghyun Park, Moontae Lee:
Enhancing Fusion-in-Decoder for Multi-Granularity Ranking. IR-RAG@SIGIR 2024: 82-86 - [c34]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: 5263-5281 - [c33]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: 5668-5680 - [c32]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: 5681-5697 - [i43]Saelyne Yang, Sunghyun Park, Yunseok Jang, Moontae Lee:
YTCommentQA: Video Question Answerability in Instructional Videos. CoRR abs/2401.17343 (2024) - [i42]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 abs/2403.14238 (2024) - [i41]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 abs/2404.17140 (2024) - [i40]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 abs/2405.01535 (2024) - [i39]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 abs/2405.04655 (2024) - [i38]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 abs/2405.11162 (2024) - [i37]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 abs/2406.05761 (2024) - [i36]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 abs/2407.01158 (2024) - [i35]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 abs/2407.19900 (2024) - [i34]Sangwoo Shin, Seunghyun Kim, Youngsoo Jang, Moontae Lee, Honguk Woo:
Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environments. CoRR abs/2408.01024 (2024) - [i33]Soyoung An, Kyunghoon Bae, Eunbi Choi, Stanley Jungkyu Choi, Yemuk Choi, Seokhee Hong, Yeonjung Hong, Junwon Hwang, Hyojin Jeon, Gerrard Jeongwon Jo, Hyunjik Jo, Jiyeon Jung, Yountae Jung, Euisoon Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Youchul Kim, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Moontae Lee, Seungjun Lee, Woohyung Lim, Sangha Park, Sooyoun Park, Yongmin Park, Boseong Seo, Sihoon Yang, Heuiyeen Yeen, Kyungjae Yoo, Hyeongu Yun:
EXAONE 3.0 7.8B Instruction Tuned Language Model. CoRR abs/2408.03541 (2024) - [i32]Sungmin Cha, Sungjun Cho, Dasol Hwang, Moontae Lee:
Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models. CoRR abs/2408.06621 (2024) - [i31]Jaehoon Lee, Hankook Lee, Sungik Choi, Sungjun Cho, Moontae Lee:
Partial-Multivariate Model for Forecasting. CoRR abs/2408.09703 (2024) - [i30]Lechen Zhang, Tolga Ergen, Lajanugen Logeswaran, Moontae Lee, David Jurgens:
SPRIG: Improving Large Language Model Performance by System Prompt Optimization. CoRR abs/2410.14826 (2024) - 2023
- [c31]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: 8334-8342 - [c30]Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee:
Unsupervised Task Graph Generation from Instructional Video Transcripts. ACL (Findings) 2023: 3392-3406 - [c29]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: 6420-6432 - [c28]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: 14389-14408 - [c27]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Few-shot Reranking for Multi-hop QA via Language Model Prompting. ACL (1) 2023: 15882-15897 - [c26]Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon:
Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR 2023: 20127-20136 - [c25]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: 783-791 - [c24]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Merging Generated and Retrieved Knowledge for Open-Domain QA. EMNLP 2023: 4710-4728 - [c23]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: 7354-7379 - [c22]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
GRACE: Discriminator-Guided Chain-of-Thought Reasoning. EMNLP (Findings) 2023: 15299-15328 - [c21]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: 14702-14729 - [c20]Yoonjoo Lee, Kyungjae Lee, Sunghyun Park, Dasol Hwang, Jaehyeon Kim, Hong-In Lee, Moontae Lee:
QASA: Advanced Question Answering on Scientific Articles. ICML 2023: 19036-19052 - [c19]Sungwoo Park, Byoungwoo Park, Moontae Lee, Changhee Lee:
Neural Stochastic Differential Games for Time-series Analysis. ICML 2023: 27269-27293 - [c18]Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee:
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. NeurIPS 2023 - [c17]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 - [i29]Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee:
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. CoRR abs/2301.02903 (2023) - [i28]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR abs/2301.11578 (2023) - [i27]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 abs/2302.03202 (2023) - [i26]Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee:
Multimodal Subtask Graph Generation from Instructional Videos. CoRR abs/2302.08672 (2023) - [i25]Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee:
Unsupervised Task Graph Generation from Instructional Video Transcripts. CoRR abs/2302.09173 (2023) - [i24]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Discriminator-Guided Multi-step Reasoning with Language Models. CoRR abs/2305.14934 (2023) - [i23]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 abs/2306.04176 (2023) - [i22]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Exploring Demonstration Ensembling for In-context Learning. CoRR abs/2308.08780 (2023) - [i21]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 abs/2309.04062 (2023) - [i20]Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee:
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning. CoRR abs/2309.04082 (2023) - [i19]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Merging Generated and Retrieved Knowledge for Open-Domain QA. CoRR abs/2310.14393 (2023) - [i18]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 abs/2310.18364 (2023) - [i17]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 abs/2311.09601 (2023) - [i16]Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee:
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. CoRR abs/2312.02615 (2023) - 2022
- [c16]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: 16952-16968 - [c15]Sangjun Han, Hyeongrae Ihm, Moontae Lee, Woohyung Lim:
Symbolic Music Loop Generation with Neural Discrete Representations. ISMIR 2022: 403-410 - [c14]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. NAACL-HLT 2022: 5493-5506 - [c13]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 - [c12]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 - [c11]Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee:
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. NeurIPS 2022 - [c10]Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. NeurIPS 2022 - [i15]Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon:
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR abs/2201.12559 (2022) - [i14]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA. CoRR abs/2205.12650 (2022) - [i13]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. CoRR abs/2205.14288 (2022) - [i12]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i11]Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. CoRR abs/2207.02505 (2022) - [i10]Sangjun Han, Hyeongrae Ihm, Moontae Lee, Woohyung Lim:
Symbolic Music Loop Generation with Neural Discrete Representations. CoRR abs/2208.05605 (2022) - [i9]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 abs/2209.02939 (2022) - [i8]Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, Minjoon Seo:
Knowledge Unlearning for Mitigating Privacy Risks in Language Models. CoRR abs/2210.01504 (2022) - [i7]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 abs/2210.15541 (2022) - 2021
- [c9]Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel:
On-the-fly Rectification for Robust Large-Vocabulary Topic Inference. ICML 2021: 6087-6097 - [i6]Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel:
On-the-Fly Rectification for Robust Large-Vocabulary Topic Inference. CoRR abs/2111.06580 (2021) - 2020
- [c8]Moontae Lee, David Bindel, David Mimno:
Prior-aware Composition Inference for Spectral Topic Models. AISTATS 2020: 4258-4268
2010 – 2019
- 2019
- [c7]Moontae Lee, Sungjun Cho, David Bindel, David Mimno:
Practical Correlated Topic Modeling and Analysis via the Rectified Anchor Word Algorithm. EMNLP/IJCNLP (1) 2019: 4990-5000 - 2018
- [b1]Moontae Lee:
Joint-Stochastic Spectral Inference for Robust Co-occurence Modeling and Latent Topic Analysis. Cornell University, USA, 2018 - 2017
- [i5]Moontae Lee, David M. Mimno:
Low-dimensional Embeddings for Interpretable Anchor-based Topic Inference. CoRR abs/1711.06826 (2017) - [i4]Moontae Lee, David Bindel, David M. Mimno:
Prior-aware Dual Decomposition: Document-specific Topic Inference for Spectral Topic Models. CoRR abs/1711.07065 (2017) - 2016
- [c6]Moontae Lee, Seok Hyun Jin, David M. Mimno:
Beyond Exchangeability: The Chinese Voting Process. NIPS 2016: 4934-4942 - [c5]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 - [i3]Paul Smolensky, Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng:
Basic Reasoning with Tensor Product Representations. CoRR abs/1601.02745 (2016) - [i2]Moontae Lee, Seok Hyun Jin, David M. Mimno:
Beyond Exchangeability: The Chinese Voting Process. CoRR abs/1610.09428 (2016) - [i1]Moontae Lee, David Bindel, David M. Mimno:
Robust Spectral Inference for Joint Stochastic Matrix Factorization. CoRR abs/1611.00175 (2016) - 2015
- [c4]Moontae Lee, David Bindel, David M. Mimno:
Robust Spectral Inference for Joint Stochastic Matrix Factorization. NIPS 2015: 2710-2718 - 2014
- [c3]David M. Mimno, Moontae Lee:
Low-dimensional Embeddings for Interpretable Anchor-based Topic Inference. EMNLP 2014: 1319-1328 - 2013
- [j1]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): 27:1-27:25 (2013) - [c2]Armand Prieditis, Moontae Lee:
When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency. MLDM 2013: 466-480 - 2012
- [c1]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
Coauthor Index
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