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cs.LG2025
Neural Weight Compression for Language Models
Jegwang Ryu, Minkyu Kim, Seungjun Shin +3
Efficient compression of language model weights is increasingly critical as model scale and deployment grow. Yet, most existing methods rely on handcrafted transforms and heuristic…
cs.CL2025
OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference
Seungjun Shin, Jaehoon Oh, Dokwan Oh
Attention mechanisms are central to the success of large language models (LLMs), enabling them to capture intricate token dependencies and implicitly assign importance to each toke…
cs.CV2025
Efficient Neural Video Representation with Temporally Coherent Modulation
Seungjun Shin, Suji Kim, Dokwan Oh
Implicit neural representations (INR) has found successful applications across diverse domains. To employ INR in real-life, it is important to speed up training. In the field of IN…