
This archive contains experiment outputs generated using the EnvTrace method for code scoring on the VISION coding datasets. Results are described in the paper "EnvTrace: Simulation-Based Semantic Evaluation of LLM Code via Execution Trace Alignment - Demonstrated at Synchrotron Beamlines" (pending release).
LLM, Machine Learning, AI Assistant, Cyber-Physical Systems, Code Assistant, Code Evaluation, Program Synthesis, Physical Systems, NLP, Synchrotron
LLM, Machine Learning, AI Assistant, Cyber-Physical Systems, Code Assistant, Code Evaluation, Program Synthesis, Physical Systems, NLP, Synchrotron
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
