mlsanityData to 7 Oct 2026

SynCPKL: Harnessing LLMs to Generate Synthetic Data for Commonsense Persona Knowledge Linking

arXiv 2407.15281 ↗First posted 21 Jul 2024cs.CLcited by 0

On the map: Synthetic data and self-improvement for LLMs → LLM synthetic data generation

Abstract (arXiv)

Understanding rich dialogues often requires NLP systems to access relevant commonsense persona knowledge, but retrieving this knowledge is challenging due to complex contexts and the implicit nature of commonsense. This paper presents our approach to the Commonsense Persona Knowledge Linking (CPKL) challenge, addressing the critical need for integrating persona and commonsense knowledge in open-domain dialogue systems. We introduce SynCPKL Pipeline, a pipeline that leverages Large Language Models to generate high-quality synthetic datasets for training commonsense persona knowledge linkers. To demonstrate the efficacy of our approach, we present SynCPKL, a new dataset specifically designed for this task. Our experiments validate the effectiveness of SynCPKL for training commonsense persona knowledge linkers. Additionally, our top-performing model, Derberta-SynCPKL, secured first place in the CPKL challenge by a 16% improvement in F1 score. We released both SynCPKL and Derberta-SynCPKL at https://github.com/irislin1006/CPKL.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in LLM synthetic data generation, one of 13 directions in Synthetic data and self-improvement for LLMs. Builds on 14 of its 24 references that are in the map. First posted on arXiv 21 Jul 2024.

Builds on

14 of 24 references.

References · 14

  1. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
  2. 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
  3. 2024Evaluating Very Long-Term Conversational Memory of LLM Agentscited by 800
  4. 2023Textbooks Are All You Need II: phi-1.5 technical reportcited by 559
  5. 2023SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agentscited by 350
  6. 2022CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilitiescited by 245
  7. 2023Orca 2: Teaching Small Language Models How to Reasoncited by 157
  8. 2023Conversation Chronicles: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversationscited by 47
  9. 2022Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterancescited by 32
  10. 2022Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Modelscited by 26
  11. 2023PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narrativescited by 19
  12. 2022DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Datasetcited by 17
2 more
  1. 2023RECIPE: How to Integrate ChatGPT into EFL Writing Educationcited by 17
  2. 2023Mind the Gap Between Conversations for Improved Long-Term Dialogue Generationcited by 13

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  1. 2026PCoKG: Personality-aware Commonsense Reasoning with Debate
  2. 2025Persona-Aware Alignment Framework for Personalized Dialogue Generation
  3. 2026The Pragmatic Persona: Discovering LLM Persona through Bridging Inference
  4. 2025Post Persona Alignment for Multi-Session Dialogue Generation
  5. 2024ConvoSense: Overcoming Monotonous Commonsense Inferences for Conversational AI
  6. 2023Faithful Persona-based Conversational Dataset Generation with Large Language Models
  7. 2023CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language Models
  8. 2023PersonaPKT: Building Personalized Dialogue Agents via Parameter-efficient Knowledge Transfer