Papers with state representation

2 papers
Natural Language-based State Representation in Deep Reinforcement Learning (2024.findings-naacl)

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Challenge: a new method for learning policies from images is proposed to reduce image-based observations' complexity and improve interpretability.
Approach: They propose a method that compresses images into a natural language form for state representation.
Outcome: The proposed method allows better interpretability and leverages processing capabilities of large-language models.
Beyond Static Persona Consistency: Dynamic Persona Coherence in LLM Role-Playing (2026.acl-long)

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Challenge: Existing LLMs conflate identity consistency with emotional rigidity . Existing models exhibit either robotic repetition or persona drift .
Approach: They propose a framework that decouples Identity-Layer Stability from Adaptive-Layer Appropriateness to achieve persona coherence repair.
Outcome: Experiments on GPT-4o, Claude-3.5-Sonnet, and DeepSeek-V3.2 show consistent improvements (+16–84% gains)

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