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Sungnyun Kim

Identifiers

  • name variant Sungnyun Kim 0.60 · backfill

Papers (20)

  1. PerMix-RLVR: Preserving Persona Expressivity under Verifiable-Reward Alignment cs.CL · 2026 · author #5
  2. MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation eess.AS · 2025 · author #3
  3. DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs cs.CL · 2025 · author #3
  4. MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition eess.AS · 2025 · author #1
  5. Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation eess.AS · 2025 · author #1
  6. DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models cs.CV · 2024 · author #1
  7. Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning cs.LG · 2024 · author #2
  8. Learning Video Temporal Dynamics with Cross-Modal Attention for Robust Audio-Visual Speech Recognition eess.AS · 2024 · author #1
  9. FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning cs.CV · 2024 · author #3
  10. DistiLLM: Towards Streamlined Distillation for Large Language Models cs.CL · 2024 · author #2
  11. STaR: Distilling Speech Temporal Relation for Lightweight Speech Self-Supervised Learning Models cs.SD · 2023 · author #2
  12. DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models cs.CV · 2023 · author #1
  13. Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification eess.AS · 2023 · author #9
  14. Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation eess.AS · 2023 · author #2
  15. Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning cs.CV · 2023 · author #1
  16. How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation cs.LG · 2022 · author #3
  17. ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning cs.CV · 2022 · author #2
  18. Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty cs.LG · 2022 · author #2
  19. Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network cs.LG · 2021 · author #2
  20. MixCo: Mix-up Contrastive Learning for Visual Representation cs.CV · 2020 · author #1

Mentions

  • 2305.15194 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2503.11026 #3 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2503.07067 #3 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2502.10447 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2504.18539 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2305.14032 #9 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2407.03563 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2410.03061 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2408.13092 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2402.03898 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2406.02355 #3 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2312.09040 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2305.11685 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2303.11101 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2106.15499 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2202.01339 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2205.05282 #2 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2205.07874 #3 · arxiv_oai · confidence 0.70 Sungnyun Kim
  • 2010.06300 #1 · arxiv_oai · confidence 0.70 Sungnyun Kim

Frequent Coauthors