ToSCA: Leveraging Hierarchical Reinforcement Learning on Temporal and Strategic Abstractions of Conversational Agents
cs.CL, cs.HC, cs.LG
Submitted: 2026-08-22
Updated: 2026-09-02
Code: https://github.com/AaronJi/ToSCA
Terminology
Sources
- OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
- Modeling the One-to-Many Property in Open-Domain Dialogue with LLMs
- A Diversity-Promoting Objective Function for Neural Conversation Models
- Dialogue Action Tokens: Steering Language Models in Goal-Directed Dialogue with a Multi-Turn Planner
- An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue Generation
- Training language models to follow instructions with human feedback
- Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought
- Self-Refine: Iterative Refinement with Self-Feedback
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
- FSM: A Finite State Machine Based Zero-Shot Prompting Paradigm for Multi-Hop Question Answering
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