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20242026
most citedFrom Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval

2 citations · 4 across the 17 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

Phase-Aware Mixture of Experts for Agentic Reinforcement Learning

Shengtian Yang, Yu Li, Shuo He +4

Reinforcement learning (RL) has equipped LLM agents with a strong ability to solve complex tasks. However, existing RL methods normally use a \emph{single} policy network, causing…

cs.AI2024

GAS: Generative Auto-bidding with Post-training Search

Yewen Li, Shuai Mao, Jingtong Gao +6

Auto-bidding is essential in facilitating online advertising by automatically placing bids on behalf of advertisers. Generative auto-bidding, which generates bids based on an adjus…

cs.AI2024

ACQ: A Deployed Two-Stage Framework for Automated Creative Quota Allocation in Large-Scale Online Advertising

Ruizhi Wang, Yu Rong, Kai Liu +4

In digital advertising, demand-side platforms (DSPs) allow advertisers to create multiple ad creatives from a single photo for real-time bidding. While increasing the number of cre…