4 papers
Diversifying RLVR Rollouts via First-Token Exploration
Soeun Kim, Albert No
Reinforcement learning with verifiable rewards (RLVR) trains reasoning models without labeled trajectories, using groups of verifier-scored rollouts to explore alternative reasonin…
Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
Yoonjun Cho, Dongjae Jeon, Soeun Kim +2
Quantization Error Reconstruction (QER) reduces accuracy loss in Post-Training Quantization (PTQ) by approximating weights as …
Assigning Distinct Roles to Quantized and Low-Rank Matrices Toward Optimal Weight Decomposition
Yoonjun Cho, Soeun Kim, Dongjae Jeon +3
Decomposing weight matrices into quantization and low-rank components () is a widely used technique for compressing large lang…
DUSK: Do Not Unlearn Shared Knowledge
Wonje Jeung, Sangyeon Yoon, Hyesoo Hong +4
Large language models (LLMs) are increasingly deployed in real-world applications, raising concerns about the unauthorized use of copyrighted or sensitive data. Machine unlearning…