LGMT is a logic-grounded metamorphic testing framework that detects hidden reasoning defects in LLMs by checking consistency on semantically invariant inputs derived from FOL equivalences.
arXiv preprint arXiv:2002.04326 , year=
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4representative citing papers
Reasoning in language models should be measured by the faithfulness and validity of their multi-step search processes and intermediate traces, not final-answer accuracy.
A competition entry achieved efficient fine-tuning of LLaMa2 70B on one GPU in 24 hours with competitive QA benchmark performance.
citing papers explorer
-
LGMT: Logic-Grounded Metamorphic Testing for Evaluating the Reasoning Reliability of LLMs
LGMT is a logic-grounded metamorphic testing framework that detects hidden reasoning defects in LLMs by checking consistency on semantically invariant inputs derived from FOL equivalences.
-
Measuring AI Reasoning: A Guide for Researchers
Reasoning in language models should be measured by the faithfulness and validity of their multi-step search processes and intermediate traces, not final-answer accuracy.
-
The nextAI Solution to the NeurIPS 2023 LLM Efficiency Challenge
A competition entry achieved efficient fine-tuning of LLaMa2 70B on one GPU in 24 hours with competitive QA benchmark performance.
- Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks