8 citations · 18 across the 11 of their papers we have counts for
6 papers · 1 filter
Exploration via Activation-Space Steering for Reinforcement Learning with Verifiable Rewards
Yunan Zeng, Jinhao Jing, Xi Cheng +1
Reinforcement learning with verifiable rewards (RLVR) trains a language model by sampling responses, scoring them with an automatic verifier, and updating the policy from the resul…
Threshold and Parity BosonSampling in the Linear-Mode Regime
Byeongseon Go, Hyunseok Jeong, Changhun Oh
BosonSampling is among the most prominent candidates for demonstrating quantum advantage. However, while the hardness of BosonSampling relies on photon-number-resolving detection,…
Hardness and Complexity Transition of Noisy Random Circuit Sampling
Byeongseon Go, Changhun Oh, Hyunseok Jeong
Random circuit sampling (RCS) is a leading candidate for demonstrating quantum advantage, supported by strong complexity-theoretic evidence of hardness in the ideal setting and by…
Improved sample complexity bound for sample-based Lindbladian simulation
Siheon Park, Youngjin Seo, Byeongseon Go +3
We establish improved sample-complexity bounds for sample-based Lindbladian simulation based on the Wave Matrix Lindbladization (WML) algorithm. For a jump operator with dimens…
Complexity phase transition for continuous-variable cluster state
Byeongseon Go, Hyunseok Jeong, Changhun Oh
Continuous-variable (CV) cluster states offer a promising platform for large-scale measurement-based quantum computations (MBQC). However, finite squeezing inevitably introduces Ga…
Quantum Metrology under Coarse-Grained Measurement
Byeong-Yoon Go, Geunhee Gwak, Young-Do Yoon +4
While quantum metrology enables measurement precision beyond classical limits, its performance is often susceptible to experimental imperfections. Most prior studies have focused o…