mlsanityData to 14 Oct 2026

TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration

arXiv 2309.16090 ↗First posted 28 Sep 2023cs.AI cs.CLcited by 11

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

  1. 2023ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models23 May
  2. 2023Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models19 Apr
  3. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity8 Feb
  4. 2022ReAct: Synergizing Reasoning and Acting in Language Models6 Oct

Other references · 32

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  4. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  5. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  6. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,947
  7. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  8. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,745
  9. 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,210
  10. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190
  11. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  12. 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 598
20 more
  1. 2018Wizard of Wikipedia: Knowledge-Powered Conversational agentscited by 530
  2. 2023ToolQA: A Dataset for LLM Question Answering with External Toolscited by 274
  3. 2023Exploring Large Language Models for Communication Games: An Empirical Study on Werewolfcited by 241
  4. 2021Internet-Augmented Dialogue Generationcited by 217
  5. 2018Decoupling Strategy and Generation in Negotiation Dialoguescited by 162
  6. 2023MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problemscited by 131
  7. 2022Long Time No See! Open-Domain Conversation with Long-Term Persona Memorycited by 108
  8. 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
  9. 2023Improving Language Models via Plug-and-Play Retrieval Feedbackcited by 87
  10. 2021Few-Shot Conversational Dense Retrievalcited by 72
  11. 2023Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Modelscited by 68
  12. 2023Building Emotional Support Chatbots in the Era of LLMscited by 62
  13. 2022Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planningcited by 60
  14. 2023Opportunities and Challenges in Neural Dialog Tutoringcited by 33
  15. 2021Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledgecited by 30
  16. 2019A Dynamic Strategy Coach for Effective Negotiationcited by 26
  17. 2022There Are a Thousand Hamlets in a Thousand People's Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memorycited by 16
  18. 2023Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillationcited by 11
  19. 2023Understanding Client Reactions in Online Mental Health Counselingcited by 9
  20. 2022PLATO-K: Internal and External Knowledge Enhanced Dialogue Generationcited by 2

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Cited by year

Citing papers per year: 2023: 3; 2024: 6; 2025: 2.

11 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2023Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration
  2. 2025DynamicMind: A Tri-Mode Thinking System for Large Language Models
  3. 2025THiNK: Can Large Language Models Think-aloud?
  4. 2025SWI: Speaking with Intent in Large Language Models
  5. 2026Reasoning Gets Harder for LLMs Inside A Dialogue
  6. 2025Attentive Reasoning Queries: A Systematic Method for Optimizing Instruction-Following in Large Language Models
  7. 2025Thinking Before You Speak: A Proactive Test-time Scaling Approach
  8. 2026CogInstrument: Modeling Cognitive Processes for Bidirectional Human-LLM Alignment in Planning Tasks