TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration
On the map: LLM reasoning → Reasoning benchmarks and evaluation
Abstract (arXiv)
Large language models (LLMs) have demonstrated exceptional performance in planning the use of various functional tools, such as calculators and retrievers, particularly in question-answering tasks. In this paper, we expand the definition of these tools, centering on conceptual tools within the context of dialogue systems. A conceptual tool specifies a cognitive concept that aids systematic or investigative thought. These conceptual tools play important roles in practice, such as multiple psychological or tutoring strategies being dynamically applied in a single turn to compose helpful responses. To further enhance the reasoning and planning capability of LLMs with these conceptual tools, we introduce a multi-persona collaboration framework: Think-Plan-Execute (TPE). This framework decouples the response generation process into three distinct roles: Thinker, Planner, and Executor. Specifically, the Thinker analyzes the internal status exhibited in the dialogue context, such as user emotions and preferences, to formulate a global guideline. The Planner then generates executable plans to call different conceptual tools (e.g., sources or strategies), while the Executor compiles all intermediate results into a coherent response. This structured approach not only enhances the explainability and controllability of responses but also reduces token redundancy. We demonstrate the effectiveness of TPE across various dialogue response generation tasks, including multi-source (FoCus) and multi-strategy interactions (CIMA and PsyQA). This reveals its potential to handle real-world dialogue interactions that require more complicated tool learning beyond just functional tools. The full code and data will be released for reproduction.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 36 of its 57 references that are in the map. First posted on arXiv 28 Sep 2023.
Builds on
36 of 57 references.
Closest ancestors · 4
Same direction, newest first
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- 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity8 Feb
- 2022ReAct: Synergizing Reasoning and Acting in Language Models6 Oct
Other references · 32
- 2020Language Models are Few-Shot Learnerscited by 32,419
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- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
- 2022Survey of Hallucination in Natural Language Generationcited by 2,075
- 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,947
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- 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,745
- 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,210
- 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190
- 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
- 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 598
20 more
- 2018Wizard of Wikipedia: Knowledge-Powered Conversational agentscited by 530
- 2023ToolQA: A Dataset for LLM Question Answering with External Toolscited by 274
- 2023Exploring Large Language Models for Communication Games: An Empirical Study on Werewolfcited by 241
- 2021Internet-Augmented Dialogue Generationcited by 217
- 2018Decoupling Strategy and Generation in Negotiation Dialoguescited by 162
- 2023MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problemscited by 131
- 2022Long Time No See! Open-Domain Conversation with Long-Term Persona Memorycited by 108
- 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
- 2023Improving Language Models via Plug-and-Play Retrieval Feedbackcited by 87
- 2021Few-Shot Conversational Dense Retrievalcited by 72
- 2023Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Modelscited by 68
- 2023Building Emotional Support Chatbots in the Era of LLMscited by 62
- 2022Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planningcited by 60
- 2023Opportunities and Challenges in Neural Dialog Tutoringcited by 33
- 2021Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledgecited by 30
- 2019A Dynamic Strategy Coach for Effective Negotiationcited by 26
- 2022There Are a Thousand Hamlets in a Thousand People's Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memorycited by 16
- 2023Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillationcited by 11
- 2023Understanding Client Reactions in Online Mental Health Counselingcited by 9
- 2022PLATO-K: Internal and External Knowledge Enhanced Dialogue Generationcited by 2
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Citing papers per year: 2023: 3; 2024: 6; 2025: 2.
11 papers.
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- 2024UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systemscited by 38
- 2024RL-GPT: Integrating Reinforcement Learning and Code-as-policycited by 32
- 2024AppBench: Planning of Multiple APIs from Various APPs for Complex User Instructioncited by 24
- 2023A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Modelscited by 23
- 2024Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Modelscited by 10
- 2023Large Language Models as Source Planner for Personalized Knowledge-grounded Dialoguecited by 6
- 2025Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Makingcited by 5
- 2025From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysiscited by 4
- 2024UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrievalcited by 3
- 2025Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Making3 Jun 2025
- 2025From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis10 Jan 2025
- 2024AppBench: Planning of Multiple APIs from Various APPs for Complex User Instruction10 Oct 2024
- 2024Tool Learning with Large Language Models: A Survey28 May 2024
- 2024Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Models5 Mar 2024
- 2024RL-GPT: Integrating Reinforcement Learning and Code-as-policy29 Feb 2024
- 2024UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval26 Feb 2024
- 2024UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systems24 Jan 2024
- 2023A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Models28 Nov 2023
- 2023Large Language Models as Source Planner for Personalized Knowledge-grounded Dialogue13 Oct 2023
- 2023Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-429 Sep 2023
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