Large Language Model Reasoning Evaluation Framework

life is chaotic, this goes slower than expected. for ideas/thoughts, lmk

Project Overview

Assess and interpret reasoning capabilities of large language models

Core Research Objectives

Reasoning Assessment Dimensions

• Logical Reasoning: evaluation of deductive and inductive reasoning
• Causal Inference: mapping reasoning pathways and decision-making processes
• Semantic Understanding: analyzing depth and nuance of contextual comprehension / text prompts
• Multimodal testing / Input-structure variation: TBD
• ** ... **: TBD

Methodological Approach

Interpretability Techniques

• Mechanistic Interpretability

  • Neuron-level level/ Attention mechanism visualization / ..

• Explainability Frameworks

  • Gradient-based mapping, LIME, SHAP (todo: cite)

Evaluation Metrics

Reasoning Performance Indicators

Metric	Description	Measurement Approach

Future Directions

• Advanced multi-modal reasoning evaluations
• Cross-model comparative studies
• Development of novel interpretability techniques

Getting Started

git clone https://github.com/CorpaciLC/LLM-reasoning.git
cd LLM-reasoning
pip install -r requirements.txt
python setup.py develop