Enhancing Reliability of Analog Neural Network Processors. - Suhong Moon; Kwanghyun Shin; Dongsuk Jeon (IEEE Trans. Very Large Scale Integr. Syst., 2019)

Advisable Learning for Self-Driving Vehicles by Internalizing Observation-to-Action Rules. - Jinkyu Kim 001; Suhong Moon; Anna Rohrbach; Trevor Darrell; John F. Canny (CVPR, 2020)

Zero-shot Visual Commonsense Immorality Prediction. - Yujin Jeong; Seongbeom Park; Suhong Moon; Jinkyu Kim (BMVC, 2022)

Judge, Localize, and Edit: Ensuring Visual Commonsense Morality for Text-to-Image Generation. - Seongbeom Park; Suhong Moon; Jinkyu Kim (CoRR, 2022)

Speculative Decoding with Big Little Decoder. - Sehoon Kim 001; Karttikeya Mangalam; Suhong Moon; Jitendra Malik; Michael W. Mahoney; Amir Gholami; Kurt Keutzer (NeurIPS, 2023)

An Embedding-Dynamic Approach to Self-Supervised Learning. - Suhong Moon; Domas Buracas; Seunghyun Park 001; Jinkyu Kim 001; John F. Canny (WACV, 2023)

Precursor ISI Cancellation Sliding-Block DFE for High-Speed Wireline Receivers. - Kunmo Kim; Suhong Moon; Jaeduk Han; Elad Alon; Ali M. Niknejad (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

Late Breaking Results: Differential and Massively Parallel Sampling of SAT Formulas. - Arash Ardakani; Minwoo Kang; Kevin He; Vighnesh M. Iyer; Suhong Moon; John Wawrzynek (DAC, 2024)

Virtual Personas for Language Models via an Anthology of Backstories. - Suhong Moon; Marwa Abdulhai; Minwoo Kang; Joseph Suh; Widyadewi Soedarmadji; Eran Kohen Behar; David M. Chan (EMNLP, 2024)

An LLM Compiler for Parallel Function Calling. - Sehoon Kim 001; Suhong Moon; Ryan Tabrizi; Nicholas Lee; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (ICML, 2024)

Text-Driven Prototype Learning for Few-Shot Class-Incremental Learning. - Seongbeom Park; Haeji Jung; Daewon Chae; Hyunju Yun; Sungyoon Kim; Suhong Moon; Jinkyu Kim 001; Seunghyun Park 001 (ICPR (9), 2024)

Localization and Manipulation of Immoral Visual Cues for Safe Text-to-Image Generation. - Seongbeom Park; Suhong Moon; Seunghyun Park 001; Jinkyu Kim 001 (WACV, 2024)

TinyAgent: Function Calling at the Edge. - Lutfi Eren Erdogan; Nicholas Lee; Siddharth Jha; Sehoon Kim 001; Ryan Tabrizi; Suhong Moon; Coleman Hooper; Gopala Anumanchipalli; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Efficient and Scalable Estimation of Tool Representations in Vector Space. - Suhong Moon; Siddharth Jha; Lutfi Eren Erdogan; Sehoon Kim 001; Woosang Lim; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors. - Joseph Suh; Suhong Moon; Minwoo Kang; David M. Chan (CoRR, 2024)

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions. - Joseph Suh; Erfan Jahanparast; Suhong Moon; Minwoo Kang; Serina Chang (ACL (1), 2025)

DEMOTIC: A Differentiable Sampler for Multi-Level Digital Circuits. - Arash Ardakani; Minwoo Kang; Kevin He; Qijing Huang 001; Vighnesh M. Iyer; Suhong Moon; John Wawrzynek (ASP-DAC, 2025)

ETS: Efficient Tree Search for Inference-Time Scaling. - Coleman Hooper; Sehoon Kim 001; Suhong Moon; Kerem Dilmen; Monishwaran Maheswaran; Nicholas Lee; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (CoRR, 2025)

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks. - Lutfi Eren Erdogan; Nicholas Lee; Sehoon Kim 001; Suhong Moon; Hiroki Furuta; Gopala Anumanchipalli; Kurt Keutzer; Amir Gholami (CoRR, 2025)

Higher-Order Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions. - Minwoo Kang; Suhong Moon; Seungyong Lee 001; Ayush Raj; Joseph Suh; David M. Chan (CoRR, 2025)