AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization | Paper Citation Record

Observation 1af7240d-0234-4d78-a8a0-7cec09e76017 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 1

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This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Is Conditional Generative Modeling all you need for Decision-Making?

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Ageneraltheoret- ical paradigm to understand learning from human preferences

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Qwen Technical Report

Reference 4

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization GAM:AGenerativeAuto-MarketingFrame- work in Online E-commerce Platforms

Reference 10

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization KTO: Model Alignment as Prospect Theoretic Optimization

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization A Survey on Mathematical Reasoning and Optimization with Large Language Models

Reference 14

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Reinforced Self-Training (ReST) for Language Modeling

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 18

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems

Reference 21

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Aunifiedsolutiontoconstrainedbiddinginonlinedisplay advertising

Reference 22

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Offline Reinforcement Learning with Implicit Q-Learning

Reference 25

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Reference 26

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Generative Auto-Bidding in Large-Scale Competitive Auctions via Diffusion Completer-Aligner

Reference 30

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Deeplandscapeforecastinginmulti-slotreal- time bidding

Reference 36

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities

Reference 40

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Auctionnet:Anovelbenchmarkfordecision-makingin large-scale games

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Making

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Voyager: An Open-Ended Embodied Agent with Large Language Models

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Reference 54

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Reference 56

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Qwen3 Technical Report

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.410995Z

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Observation aa5ac641-ba4f-4401-a587-592e1f1a7b29 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization ReAct: Synergizing Reasoning and Acting in Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.487336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a0ac16b-ef37-488b-ade4-f27ba5baeba1 · outbound

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Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.566835Z

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Unavailable: canonical work link unavailable.

Observation 996a11c2-e82c-4598-92a5-cde907296e77 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.632023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28eb0e5b-dc1a-4958-b5ec-ffa632a621b0 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.728363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99906e1e-b35a-430e-a39a-50b0cfcc7171 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.818855Z

Source-reported events for the cited work

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Observation bad7ab3a-08bd-44c9-b43c-7c7cc7130940 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.873449Z

Source-reported events for the cited work

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Observation befd8fcf-4af2-49a5-8d38-8aec57f01bbf · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.927545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e333b88-aea9-4eb9-a05f-25dd318dbf20 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization On the Role of Language Representations in Auto-Bidding: Findings and Implications

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:49.033713Z

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Observation 8356e9c8-7916-4ec7-ab23-bf70784a89b0 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:48.959680Z

Source-reported events for the cited work

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Observation dbed28c8-9077-46ff-b417-37680b27efe9 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Unresolved cited work

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:49.142233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edf69f15-12c2-4c98-825c-abc8331cbc08 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Provide ⟨M⟩distinctstrategiesrankedbypotentialvalueindescending order; they must differ in at least one strategy dimension

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:49.201550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 880f78b4-9a5b-4510-a87f-25a21608db92 · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Advances in Neural Information Processing Systems 34 (2021), 17777–17788

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:44.245497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78223732-b189-46e3-9daf-847b37a1b68b · outbound

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AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization Generative Bid Shading in Real-Time Bidding Advertising

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:45.785409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a16450a5-17e4-475b-bb8a-bb407235337a · outbound

This paper cites In Proceedings of the ACM Web Conference 2026.

AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization In Proceedings of the ACM Web Conference 2026

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-01T18:32:46.367637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Outbound references

Pith citing papers