Local Space-Time Smoothing for Version Controlled Documents. - Seungyeon Kim 001; Guy Lebanon (COLING (Posters), 2010)

Local Space-Time Smoothing for Versioned Documents - Seungyeon Kim 001; Guy Lebanon (CoRR, 2010)

Automatic Feature Induction for Stagewise Collaborative Filtering. - Joonseok Lee; Mingxuan Sun; Seungyeon Kim 001; Guy Lebanon (NIPS, 2012)

Cumulative Revision Map - Seungyeon Kim 001; Joshua V. Dillon; Guy Lebanon (CoRR, 2012)

Beyond Sentiment: The Manifold of Human Emotions. - Seungyeon Kim 001; Fuxin Li; Guy Lebanon; Irfan A. Essa (AISTATS, 2013)

Local Low-Rank Matrix Approximation. - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (ICML (2), 2013)

Matrix Approximation under Local Low-Rank Assumption - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (ICLR (Workshop Poster), 2013)

The Manifold of Human Emotions - Seungyeon Kim 001; Fuxin Li; Guy Lebanon; Irfan A. Essa (ICLR (Workshop Poster), 2013)

Local collaborative ranking. - Joonseok Lee; Samy Bengio; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (WWW, 2014)

Fast Spammer Detection Using Structural Rank. - Seungyeon Kim 001; Haesun Park; Guy Lebanon (CoRR, 2014)

Estimating Temporal Dynamics of Human Emotions. - Seungyeon Kim 001; Joonseok Lee; Guy Lebanon; Haesun Park (AAAI, 2015)

Local Context Sparse Coding. - Seungyeon Kim 001; Joonseok Lee; Guy Lebanon; Haesun Park (AAAI, 2015)

Novel document representations based on labels and sequential information. - Seungyeon Kim 001 (2015)

LLORMA: Local Low-Rank Matrix Approximation. - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer; Samy Bengio (J. Mach. Learn. Res., 2016)

Why ADAM Beats SGD for Attention Models. - Jingzhao Zhang; Sai Praneeth Karimireddy; Andreas Veit; Seungyeon Kim 001; Sashank J. Reddi; Sanjiv Kumar; Suvrit Sra (CoRR, 2019)

Semantic Label Smoothing for Sequence to Sequence Problems. - Michal Lukasik; Himanshu Jain; Aditya Krishna Menon; Seungyeon Kim 001; Srinadh Bhojanapalli; Felix X. Yu; Sanjiv Kumar (EMNLP (1), 2020)

Why are Adaptive Methods Good for Attention Models? - Jingzhao Zhang; Sai Praneeth Karimireddy; Andreas Veit; Seungyeon Kim 001; Sashank J. Reddi; Sanjiv Kumar; Suvrit Sra (NeurIPS, 2020)

Why distillation helps: a statistical perspective. - Aditya Krishna Menon; Ankit Singh Rawat; Sashank J. Reddi; Seungyeon Kim 001; Sanjiv Kumar (CoRR, 2020)

RankDistil: Knowledge Distillation for Ranking. - Sashank J. Reddi; Rama Kumar Pasumarthi; Aditya Krishna Menon; Ankit Singh Rawat; Felix X. Yu; Seungyeon Kim 001; Andreas Veit; Sanjiv Kumar (AISTATS, 2021)

Evaluations and Methods for Explanation through Robustness Analysis. - Cheng-Yu Hsieh; Chih-Kuan Yeh; Xuanqing Liu; Pradeep Kumar Ravikumar; Seungyeon Kim 001; Sanjiv Kumar; Cho-Jui Hsieh (ICLR, 2021)

A statistical perspective on distillation. - Aditya Krishna Menon; Ankit Singh Rawat; Sashank J. Reddi; Seungyeon Kim 001; Sanjiv Kumar (ICML, 2021)

On the Reproducibility of Neural Network Predictions. - Srinadh Bhojanapalli; Kimberly Wilber; Andreas Veit; Ankit Singh Rawat; Seungyeon Kim 001; Aditya Krishna Menon; Sanjiv Kumar (CoRR, 2021)

Balancing Robustness and Sensitivity using Feature Contrastive Learning. - Seungyeon Kim 001; Daniel Glasner; Srikumar Ramalingam; Cho-Jui Hsieh; Kishore Papineni; Sanjiv Kumar (CoRR, 2021)

In defense of dual-encoders for neural ranking. - Aditya Krishna Menon; Sadeep Jayasumana; Ankit Singh Rawat; Seungyeon Kim 001; Sashank J. Reddi; Sanjiv Kumar (ICML, 2022)

Supervision Complexity and its Role in Knowledge Distillation. - Hrayr Harutyunyan; Ankit Singh Rawat; Aditya Krishna Menon; Seungyeon Kim 001; Sanjiv Kumar (ICLR, 2023)

Teacher Guided Training: An Efficient Framework for Knowledge Transfer. - Manzil Zaheer; Ankit Singh Rawat; Seungyeon Kim 001; Chong You; Himanshu Jain; Andreas Veit; Rob Fergus; Sanjiv Kumar (ICLR, 2023)

Efficient Training of Language Models using Few-Shot Learning. - Sashank J. Reddi; Sobhan Miryoosefi; Stefani Karp; Shankar Krishnan; Satyen Kale; Seungyeon Kim 001; Sanjiv Kumar (ICML, 2023)

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. - Seungyeon Kim 001; Ankit Singh Rawat; Manzil Zaheer; Sadeep Jayasumana; Veeranjaneyulu Sadhanala; Wittawat Jitkrittum; Aditya Krishna Menon; Rob Fergus; Sanjiv Kumar (CoRR, 2023)

Analysis of Plan-based Retrieval for Grounded Text Generation. - Ameya Godbole; Nicholas Monath; Seungyeon Kim 001; Ankit Singh Rawat; Andrew McCallum; Manzil Zaheer (EMNLP, 2024)

USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. - Seungyeon Kim 001; Ankit Singh Rawat; Manzil Zaheer; Wittawat Jitkrittum; Veeranjaneyulu Sadhanala; Sadeep Jayasumana; Aditya Krishna Menon; Rob Fergus; Sanjiv Kumar (ICML, 2024)

A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. - Ankit Singh Rawat; Veeranjaneyulu Sadhanala; Afshin Rostamizadeh; Ayan Chakrabarti; Wittawat Jitkrittum; Vladimir Feinberg; Seungyeon Kim 001; Hrayr Harutyunyan; Nikunj Saunshi; Zachary Nado; Rakesh Shivanna; Sashank J. Reddi; et al. (CoRR, 2024)

Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA. - Sangmin Bae; Adam Fisch; Hrayr Harutyunyan; Ziwei Ji; Seungyeon Kim 001; Tal Schuster (ICLR, 2025)

Faster Cascades via Speculative Decoding. - Harikrishna Narasimhan; Wittawat Jitkrittum; Ankit Singh Rawat; Seungyeon Kim 001; Neha Gupta; Aditya Krishna Menon; Sanjiv Kumar (ICLR, 2025)