{
  "id": 66880,
  "title": "MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models",
  "url": "https://urgent.news/2026/07/31/mot-sr-multi-objective-tool-augmented-scientific-equation-discovery",
  "topic": "ai",
  "section": "AI",
  "published": "2026-07-31T15:52:07.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2607.29561v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Symbolic Regression (SR) aims to discover analytical equations from observational data and plays a central role in scientific modeling. While recent Large Language Model (LLM) based approaches show promise, they face two limitations. First, they lack data analysis mechanisms for uncovering variable dependencies, which reduces the efficiency of equation discovery. Second, most methods rely on…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}