Daehyeok Kim — accepted AI-conference papers

2025

ConfigBot: Adaptive Resource Allocation for Robot Applications in Dynamic Environments

Rohit Dwivedula, Sadanand Modak, Aditya Akella, Joydeep Biswas, Daehyeok Kim, Christopher J. Rossbach

IROS 2025

The growing use of service robots in dynamic environments requires flexible management of on-board compute resources to optimize the performance of diverse tasks such as navigation, localization, and perception. Current robot deployments often rely on static OS configurations and system over-provisi

Cited by 1 Source ↗code ↗Scholar ↗

2025

Large Language Models as Realistic Microservice Trace Generators

Donghyun Kim, Sriram Ravula, Taemin Ha, Alex Dimakis, Daehyeok Kim, Aditya Akella

EMNLP 2025

Workload traces are essential to understand complex computer systems’ behavior and manage processing and memory resources. Since real-world traces are hard to obtain, synthetic trace generation is a promising alternative. This paper proposes a first-of-a-kind approach that relies on training a large

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2023

Counterfactual Two-Stage Debiasing For Video Corpus Moment Retrieval

Sunjae Yoon, Ji Woo Hong, SooHwan Eom, Hee Suk Yoon, Eunseop Yoon, Daehyeok Kim +3

ICASSP 2023accepted

Video Corpus Moment Retrieval aims to select a temporal video moment pertinent to a given language query from a large video corpus. Existing systems are prone to rely on a retrieval bias as a shortcut, which hinders the systems from accurately learning vision-language association. The retrieval bias…

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