5 citations · 13 across the 11 of their papers we have counts for
13 papers
Kwai Summary Attention V2 Technical Report
OneRec Team, Chenglong Chu, Guohong Mu +30
Summary-token architectures such as Kwai Summary Attention (KSA) compress distant context into learnable Summary token per chunk, and hybrid variants interleave these layers with f…
KUAISHOU Explorer LLM-Rec Challenge 2026: Reasoning Generative Recommendation
Jiangxia Cao, Hao Peng, Wenlong Xu +97
Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recom…
Breaking the Curse of Repulsion: Remoteness-Aware Control of Negative Off-Policy Updates
Yusen Huo, Changping Wang, Yangru Huang +2
Off-policy policy optimization reuses historical behavior, including negative-advantage samples that suppress known failures. We show that repeated reuse can turn this useful signa…
DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs
Mingxuan Song, Yusen Huo, Bohan Zhou +5
Optimizing the advertiser's cumulative value of winning impressions under budget constraints poses a complex challenge in online advertising, under the paradigm of AI-Generated Bid…
DecisionLLM: Large Language Models for Long Sequence Decision Exploration
Xiaowei Lv, Zhilin Zhang, Yijun Li +10
Long-sequence decision-making, which is usually addressed through reinforcement learning (RL), is a critical component for optimizing strategic operations in dynamic environments,…
Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens
Jiahao Ji, Tianyu Wang, Yeshu Li +5
Auto-bidding is crucial in facilitating online advertising by automatically providing bids for advertisers. While previous work has made great efforts to model bidding environments…
An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising
Zhijian Duan, Yusen Huo, Tianyu Wang +6
In online advertising, advertisers commonly utilize auto-bidding services to bid for impression opportunities. A typical objective of the auto-bidder is to optimize the advertiser'…
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
Kefan Su, Yusen Huo, Zhilin Zhang +5
Decision-making in large-scale games is an essential research area in artificial intelligence (AI) with significant real-world impact. However, the limited access to realistic larg…
AIGB: Generative Auto-bidding via Conditional Diffusion Modeling
Jiayan Guo, Yusen Huo, Zhilin Zhang +5
Auto-bidding plays a crucial role in facilitating online advertising by automatically providing bids for advertisers. Reinforcement learning (RL) has gained popularity for auto-bid…
Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding
Haoming Li, Yusen Huo, Shuai Dou +5
In online advertising, advertisers participate in ad auctions to acquire ad opportunities, often by utilizing auto-bidding tools provided by demand-side platforms (DSPs). The curre…
Sustainable Online Reinforcement Learning for Auto-bidding
Zhiyu Mou, Yusen Huo, Rongquan Bai +4
Recently, auto-bidding technique has become an essential tool to increase the revenue of advertisers. Facing the complex and ever-changing bidding environments in the real-world ad…
DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning
Xianyuan Zhan, Haoran Xu, Yue Zhang +3
Optimizing the combustion efficiency of a thermal power generating unit (TPGU) is a highly challenging and critical task in the energy industry. We develop a new data-driven AI sys…
Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep Reinforcement Learning and Imitation Learning
Yusen Huo, Qinghua Tao, Jianming Hu
Traffic signal control has long been considered as a critical topic in intelligent transportation systems. Most existing learning methods mainly focus on isolated intersections and…