Papers with rule generation

2 papers
Can LLMs Reason with Rules? Logic Scaffolding for Stress-Testing and Improving LLMs (2024.acl-long)

Copied to clipboard

Challenge: Large language models (LLMs) have impressive human-like performance across various reasoning tasks, but their mastery of underlying inferential rules falls short of human capabilities.
Approach: They propose a logic scaffolding inferential rule generation framework to construct an infer- ential rule base, ULogic, comprising both primitive and compositional rules across five domains.
Outcome: The proposed model improves the ability to generate accurate, complex and abstract conclusions and premises and improves various commonsense reasoning tasks.
CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs (2026.acl-long)

Copied to clipboard

Challenge: Recent advances in large language models (LLMs) have enabled more sophisticated content moderation, but these methods lack generalization, interpretability, and adaptability to unseen or ambiguous cases.
Approach: They propose a new moderation framework that leverages analogical examples to enhance rule induction and decision reliability.
Outcome: The proposed method outperforms rule-injected fine-tuning baselines and multi-stage static RAG pipelines in terms of moderation accuracy and rule quality.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations