Papers with greedy strategies

2 papers
Look Twice before You Leap: A Rational Framework for Localized Adversarial Text Anonymization (2026.findings-acl)

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Challenge: Existing LLMs rely on remote API services, which creates privacy paradoxes and suboptimal solutions with severe utility collapse.
Approach: They propose a localized and training-free framework with an Attacker-Arbitrator-Anonymizer architecture that allows attackers to filter out ghost leaks.
Outcome: The proposed framework achieves superior privacy-utility trade-off compared to strong baselines.
Navigating the Infinite Dynamic Web Space: Effective In-Context Exploration via Cognitive Multi-Agent Collaboration (2026.eacl-long)

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Challenge: Existing methods for dynamic web navigation rely on greedy strategies or value estimation, struggle to achieve effective backtracking and are heavily dependent on proprietary models.
Approach: They propose a cognitive multi-agent collaboration framework that enhances cyberspace exploration capability through In-Context Exploration.
Outcome: The proposed framework surpasses the proprietary model Claude-3.5 Sonnet on the WebArena benchmark.

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