6 papers indexed
Xubo Liu, Wenya Guo, Ruxue Yan, Xinying Qian, Ying Zhang
LLM preference alignment aims to optimize models toward human preferences across diverse user instructions. Reinforcement learning has become a major post-training approach for this goal, but existing proxy rewards are often outcome-level, mainly evaluating the final response whi…
Ying Zhang, Fan Liu, Yifeng Xiong, Jie Yang, Xinyi Wang, Shi Jin
This paper investigates the ranging performance of a bistatic integrated sensing and communications (ISAC) system employing orthogonal frequency-division multiplexing (OFDM), in which an ISAC transmitter emits a communication waveform carrying random data symbols, and a separate…
Jialin Wu, Fan Liu, Ying Zhang, Yifeng Xiong, Jie Yang, Shi Jin
This paper investigates the statistical ambiguity functions (AFs) of orthogonal frequency division multiplexing (OFDM) waveforms that incorporate deterministic unit-modulus pilot symbols and random data payloads for integrated sensing and communication (ISAC). We derive analytica…
In this paper, we propose a novel tamed stochastic gradient Hamiltonian Monte Carlo (tSGHMC) algorithm for sampling and stochastic optimization problems with superlinearly growing stochastic gradients. Under a certain continuity in average condition and a strong convexity conditi…
Sungjoo Chung, Ying Zhang, Meng Yue, Hantao Cui
Black-box modeling of inverter-based resources (IBRs) has attracted growing interest for real-time grid operation and control in the presence of proprietary electronic control architectures. Existing machine learning (ML)-based online dynamic trajectory prediction approaches usin…
Xiaomin Li, Qian Liang, Yinan Li, Ying Zhang, Chen Li, Jing Lyu, et al.
Reinforcement Learning like Group Relative Policy Optimization (GRPO) has significantly advanced text-to-image post-training. However, current methods often favor superficial aesthetics, such as over-saturated colors, leaving critical flaws like AI artifacts and biological implau…