StateTree: Enhancing Long-Term Dialogue Reasoning via Reinforcement Learning

arXiv:2609.38809 · cs.CL, cs.AI · Submitted 2026-09-30 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/bluedream02/StateTree

Terminology

• Benchmark — 20× in this paper · explained in 2 episodes
• Temporal Reasoning — 15× in this paper · explained in 2 episodes
• Ablation — 13× in this paper · explained in 1 episode
• Accuracy — 12× in this paper · explained in 1 episode
• Multi-hop Reasoning — 11× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• GRPO — 7× in this paper · explained in 6 episodes
• Trace — 7× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Reward Function — 5× in this paper · explained in 2 episodes
• F1 Score — 4× in this paper · explained in 3 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 3× in this paper · explained in 5 episodes
• Core — 3× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 3× in this paper · explained in 3 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• LLM judge — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Group Relative Policy Optimization — 1× in this paper
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Hacking — 1× in this paper · explained in 8 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes

Sources

• LongReason: A Synthetic Long-Context Reasoning Benchmark via Context Expansion
• DeepSeek-V3 Technical Report
• MiniMax-01: Scaling Foundation Models with Lightning Attention
• YaRN: Efficient Context Window Extension of Large Language Models
• LongRoPE2: Near-Lossless LLM Context Window Scaling
• APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
• ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
• SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale
• Large Language Models Can Self-Improve in Long-context Reasoning
• QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
• Qwen2 Technical Report
• Qwen3 Technical Report
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale
• Measuring Massive Multitask Language Understanding
• Let's Verify Step by Step
• Instruction-Following Evaluation for Large Language Models
• GPT-4o System Card

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