Enhancing LLMs in Predictive Political QA with Semi-Structured Data
[Sztuczna inteligencja] Autorzy: Yinan Liu, Zihan Zhou, Zichun Jin i 3 więcej
Predictive political question answering (QA), such as predicting how a political actor will vote, goes beyond factual lookup. External political resources offer rich historical evidence, but rarely contain the answer itself. Existing LLM augmentation methods, including actor-profile-based simulation and knowledge graph evidence injection, improve political reasoning but largely treat external resources as knowledge-based evidence, leaving prediction-relevant signals under-modeled. We identify two complementary signals for predictive political QA: actor stances that capture issue-specific preferences, and high-order structure signals that capture indirect dependencies among political actors. We propose PSL, a dual-view framework that converts semi-structured political records into inference-oriented evidence for LLMs. PSL extracts stance signals from question-relevant actor records in a …
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja