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Kyuhong Shim

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Articles

BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference

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By Janghyeon Kim, Minsoo Kim, Kyuhong Shim
| huggingface.co
Get this paper in your agent: hf papers read 2609.04971 Don't have the latest CLI? curl -LsSf https://hf.co/cli/install.sh | bash Models citing this paper 0 No model linking this paper Cite arxiv.org/abs/2609.04971 in a model README.md to link it from this page. Datasets citing this paper 0 No dataset linking this paper Cite arxiv.org/abs/2609.04971 in a dataset README.md to link it from this page.
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Computer Science > Machine Learning

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By Minsoo Kim, Kyuhong Shim, Jungwook Choi
| arXiv
Large Reasoning Models (LRMs) achieve superior problem-solving through extended Chain-of-Thought (CoT) generation, but the resulting key-value (KV) cache grows linearly with sequence length and creates severe memory bottlenecks, often exceeding GPU capacity for long reasoning traces. Existing KV cache compression methods rely on recent queries to estimate future token importance, implicitly assuming these serve as reliable proxies for future attention patterns.
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Computer Science > Artificial Intelligence

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By Jeonghyeon Kim, Kyuhong Shim, Hyojung Gwon
| arXiv
Coding agents are now commonly evaluated on the SWE-bench family of benchmarks, whose tasks are built from curated GitHub issues--long, structured, and information-rich. Real user requests, however, are typically far shorter and less structured.
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