LLM-SRBENCH
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Symbolic Regression | LLM-SRBench (phys_osc) | Best Reward8.9985 | 16 | |
| Symbolic Regression | LLM-SRBench matsci | Best Reward8.25 | 16 | |
| Symbolic Regression | LLM-SRBench chem_react | Best Reward9 | 16 | |
| Symbolic Regression | LLM-SRBench bio_pop_growth | Best Reward8.9725 | 16 | |
| Symbolic Regression | LLM-SRBench Symbolic | Term Recall34.4 | 14 | |
| Symbolic Regression | LLM-SRBench OOD (test) | NMSE0.325 | 14 | |
| Symbolic Regression | LLM-SRBench ID (test) | NMSE0.4 | 14 | |
| Symbolic Regression | LLM-SRBENCH LSR-Transform | NMSE0.067 | 13 | |
| Numerical Symbolic Regression | LLM-SRBench 129-task synthetic (test) | Chemistry 95% Acc (Tol=0.01)35 | 11 | |
| Symbolic Regression | LLM-SRBench LSR-Synth Biology | NMSE0.64 | 10 | |
| Symbolic Regression | LLM-SRBench LSR-Synth Chemistry | NMSE0.0002 | 10 | |
| Symbolic Regression | LLM-SRBENCH LSR-Syn | Chemistry Error0 | 9 | |
| Symbolic Regression | LLM-SRBench (official 239-problem split) | Acc0.1 (%)77 | 6 | |
| Symbolic Regression | LLM-SRBench 129-task synthetic subset OOD (test) | Chemistry Accuracy (Tol 0.01)32 | 5 | |
| Symbolic Regression | LLM-SRBench Overall | Median R20.875 | 3 | |
| Symbolic Regression | LLM-SRBench Transform | Median R21.253 | 3 | |
| Symbolic Regression | LLM-SRBench Synthetic | Median R20.984 | 3 |
Showing 17 of 17 rows