collaborators

14 papers

cs.SI2026

Policy-Embedded Graph Expansion: Networked HIV Testing with Diffusion-Driven Network Samples

Akseli Kangaslahti, Davin Choo, Lingkai Kong +3

HIV is a retrovirus that attacks the human immune system and can lead to death without proper treatment. In collaboration with the WHO and the University of Witwatersrand, we study…

cs.LG2026

Reward Shaping for (Inference-Time) Alignment: A Stackelberg Game Perspective

Haichuan Wang, Tao Lin, Lingkai Kong +3

Existing alignment methods directly use the reward model learned from user preference data to optimize an LLM policy, subject to KL regularization with respect to the base policy.…

cs.LG2026

Generative Frontier Planning for Adaptive Peer-Referral Recruitment under Covariate-Dependent Arrivals

Lingkai Kong, Hezi Jiang, Andrew Ma +3

Peer-referral recruitment systems such as respondent-driven sampling are critical for studying and intervening on hidden populations affected by infectious diseases. To accelerate…

cs.LG2026

Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions

Lingkai Kong, Anagha Satish, Hezi Jiang +6

Reinforcement learning (RL) with combinatorial action spaces remains challenging because feasible action sets are exponentially large and governed by complex feasibility constraint…

cs.AI2026

How LLMs Are Persuaded: A Few Attention Heads, Rerouted

Xiangkun Sun, Lingkai Kong, Aoqi Zhang +2

Language models can be persuaded to abandon factual knowledge. This vulnerability is central to AI safety, but its internal mechanism remains poorly understood. We uncover a compac…

cs.LG2026

LLM Advertisement based on Neuron Auctions

Peiran Yun, Wenxin Xu, Jiayuan Liu +4

As Large Language Models (LLMs) transition into conversational agents, generative advertising emerges as a crucial monetization strategy. However, embedding advertisements within u…