Frontier DataText

2023 Howard University Physics Graduate Qualifying Exam–Based Reasoning SFT Dataset

Type
CoT Reasoning Dataset
Domain
Science and Engineering
Language
English

Overview

This supervised fine-tuning (SFT) dataset is built from the 2023 Howard University Physics Graduate Qualifying Exam, pairing questions in classical mechanics, electromagnetism, quantum mechanics, and statistical mechanics with full step-by-step solutions.

Potential Use Cases

  • Supervised Fine-Tuning for Scientific Reasoning: Trains LLMs to carry out multi-step, physically grounded derivations across the four core areas of graduate physics, including the operator formalism and ensemble arguments that answer-only data fails to teach.
  • Subfield-Resolved Capability Diagnosis: Enables evaluation broken out by classical mechanics, electromagnetism, quantum mechanics, and statistical mechanics, exposing which domains a model reasons through reliably and which it merely approximates.
Flitto Curation Data Flitto Curation Data