Papers with natural language problem
Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have shown human-like reasoning abilities but struggle with complex logical problems. |
| Approach: | They propose a framework which integrates large language models with symbolic solvers to improve logical problem-solving by combining them with a self-refinement module. |
| Outcome: | The proposed framework improves logical problem-solving by integrating LLMs with symbolic solvers. |
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs (2024.emnlp-main)
Copied to clipboard
| Challenge: | Recent prompting techniques have improved LLMs’ performance on various reasoning tasks, but there is little understanding of what triggers reasoning abilities in LLM in the inference stage. |
| Approach: | They propose a method that transforms a natural language problem into code and directly prompts the LLM using the generated code without resorting to external code execution. |
| Outcome: | The proposed method boosts multiple LLMs by 22.52 percentage points on GPT 3.5, 7.75 on Mixtral, and 16.78 on Mistral. |