1 citations · 1 across the 14 of their papers we have counts for
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SCA: Spatial Credit Assignment for Reinforcement Learning of GUI Agents
Shengtian Yang, Ziyu Xiong, Kaibing Yang +6
GUI agents automate tasks on digital devices by grounding language instructions in visual interfaces. Existing group-relative reinforcement learning improves GUI action prediction…
Dr. Free: You Don't Need Difficulty Rewards for Self-Evolving Search Agents
Zhipeng Qian, Zihan Liang, Yufei Ma +10
A central limitation of current data-free self-evolution methods for training search agents is their reliance on difficulty-based proposer rewards. These methods reward a proposer…
OneBid: A Unified Auto-Bidding Foundation Model for Diverse oCPX Advertising Scenarios
Yewen Li, Peng Jiang, Yitian Li +3
Auto-bidding is central to computational advertising, where strategies must maximize advertisers' conversion value under economic constraints. It has evolved from rule-based contro…
SRPO: Setwise Relative Policy Optimization for Multi-Agent Systems
Shengtian Yang, Ziyu Xiong, Yu Li +3
Multi-agent systems enable complex reasoning and tool use by coordinating agents that divide roles and refine candidate solutions. Existing methods typically update individual agen…
AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories
Zhiyi Lyu, Yewen Li, Longtao Zheng +7
LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundamentally difficult: real-world…
Hierarchical Residual Policy Optimization for Generative Recommendations
Kaifeng Guo, Yiming Yang, Jingtong Gao +6
Generative recommenders select items by autoregressively decoding semantic identifiers (SIDs), whose token positions induce a coarse-to-fine hierarchy over the item space. In pract…
PlatformBid: An Auto-Bidding Benchmark from a Unified Advertising Platform's Perspective
Shengtian Yang, Yewen Li, Peng Jiang +4
Real-time bidding is central to computational advertising, comprising three elements: Supply Side Platform (SSP) selling ad impressions, Demand Side Platform (DSP) bidding for adve…
Reinforced Preference Optimization for Reasoning-Augmented Recommendations
Jingtong Gao, Zeyu Song, Chi Lu +7
Recommender systems are critical for delivering personalized content across digital platforms, and recent advances in Large Language Models (LLMs) offer new opportunities to enhanc…
Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation
Jiaju Chen, Chongming Gao, Chenxiao Fan +4
Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without c…
LBM: Hierarchical Large Auto-Bidding Model via Reasoning and Acting
Yewen Li, Zhiyi Lyu, Peng Jiang +3
The growing scale of ad auctions on online advertising platforms has intensified competition, making manual bidding impractical and necessitating auto-bidding to help advertisers a…