Symbolic Regression on LSR-Synth Physics
0.0001NMSEPiT-PO
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| PiT-POBackbone=Llama-3.1-8B-Instruct2026.02 | 0.0001 | 11.36 | 40.91 | — | |
| LLM-SR+Backbone=Qwen2.5-7B, Optimization Strategy=SAGE-Fit (Inner-loop)2026.05 | 0.0001 | 11.36 | 48 | — | |
| LLM-SRBackbone=Qwen2.5-7B, Optimization Strategy=Post-hoc Refinement2026.05 | 0.0001 | 4.55 | 36.84 | — | |
| LLM-SRBackbone=Llama-3.1-8B-Instruct2026.02 | 0.0001 | 6.97 | 34.09 | — | |
| Deliberate EvolutionBackbone=Qwen3-4B-Instruct-25072026.06 | 0.0004 | — | — | 15.91 | |
| Deliberate EvolutionBackbone=Llama3.1-8B-Instruct2026.06 | 0.001 | — | — | 11.36 | |
| LaSRBackbone=Llama-3.1-8B-Instruct2026.02 | 0.0018 | 4.54 | 25.02 | — | |
| LLM-SRBackbone=Qwen3-4B-Instruct-25072026.06 | 0.0025 | — | — | 6.82 | |
| PySR+Optimization Strategy=SAGE-Fit (Inner-loop)2026.05 | 0.0029 | 2.27 | 52.63 | — | |
| LLM-SRBackbone=Llama3.1-8B-Instruct2026.06 | 0.003 | — | — | 6.82 | |
| LaSR+Backbone=Qwen2.5-7B, Optimization Strategy=SAGE-Fit (Inner-loop)2026.05 | 0.0039 | 6.81 | 9.09 | — | |
| PySROptimization Strategy=Post-hoc Refinement2026.05 | 0.0048 | 0 | 16 | — | |
| uDSR+Optimization Strategy=SAGE-Fit (Inner-loop)2026.05 | 0.0048 | 2.27 | 12.5 | — | |
| LaSRBackbone=Qwen2.5-7B, Optimization Strategy=Post-hoc Refinement2026.05 | 0.006 | 2.27 | 6.82 | — | |
| LASRBackbone=Qwen3-4B-Instruct-25072026.06 | 0.006 | — | — | 6.82 | |
| LASRBackbone=Llama3.1-8B-Instruct2026.06 | 0.0061 | — | — | 9.09 | |
| LLMDirectBackbone=Llama3.1-8B-Instruct2026.06 | 0.01 | — | — | 0 | |
| uDSROptimization Strategy=Post-hoc Refinement2026.05 | 0.0119 | 0 | 7.5 | — | |
| Direct PromptingBackbone=Llama-3.1-8B-Instruct2026.02 | 0.0459 | 0 | 0 | — | |
| LLMDirectBackbone=Qwen3-4B-Instruct-25072026.06 | 0.0546 | — | — | 6.82 | |
| SGABackbone=Qwen3-4B-Instruct-25072026.06 | 0.104 | — | — | 0 | |
| SGABackbone=Llama-3.1-8B-Instruct2026.02 | 0.1549 | 0 | 2.27 | — | |
| SGABackbone=Llama3.1-8B-Instruct2026.06 | 0.155 | — | — | 2.27 |