uqlm and kernel-language-entropy

Both tools offer distinct approaches to uncertainty quantification for language models, with UQLM focusing on Python-packaged UQ-based hallucination detection and kernel-language-entropy providing code for fine-grained UQ from semantic similarities, making them **complementary** in the broader LLM-reasoning-research landscape as they address different facets of the same problem.