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Sangwoo Kang

2 accepted papers

2025

Exploration-Driven Reinforcement Learning for Expert Routing Improvement in Mixture-of-Experts Language Models

EMNLP 2025

The performance of MoE-based LLMs depends on the router’s ability to select suitable experts; however, the router is typically not explicitly supervised to acquire this routing ability. We propose Exploration-Driven Reinforcement Learning (ERL), which explicitly optimizes the router by exploration o

2025

FractalLLM: Lossless Self-Speculative Decoding with Layer Embedded Self-Compression

EMNLP 2025

Autoregressive decoding in large language models (LLMs) necessitates a full forward pass for each generated token, significantly increasing inference latency. To address this limitation, we propose Fractal-LLM, a lossless self-speculative decoding method that embeds a compressed model within selecte

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