{
  "id": "2606.32029",
  "title": "When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors",
  "first_seen": "2026-07-02",
  "published_date": "2026-06-30",
  "observed_dates": [
    "2026-07-02"
  ],
  "score": {
    "novelty": 100,
    "practical_impact": 94,
    "technical_depth": 100,
    "implementation_potential": 69,
    "relevance": 84,
    "community_signal": 38,
    "summary_confidence": 95,
    "overall": 85,
    "weights": {
      "novelty": 0.2,
      "practical_impact": 0.2,
      "technical_depth": 0.15,
      "implementation_potential": 0.15,
      "relevance": 0.15,
      "community_signal": 0.1,
      "summary_confidence": 0.05
    }
  },
  "recommendation": "Read",
  "categories": [
    "F1 score",
    "answer accuracy",
    "critic-based filtering",
    "data referencing errors",
    "in-distribution",
    "large language models"
  ],
  "innovation_summary": "When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors: In this work, we present the first systematic evaluation of tabular data referencing errors across different models and tasks.",
  "why_it_matters": [
    "Overall signal 85/100 driven by novelty 100 and practical impact 94.",
    "Primary categories: F1 score, answer accuracy, critic-based filtering, data referencing errors, in-distribution, large language models.",
    "Community signal includes 3 upvote(s) and 1 comment(s), which helps separate durable interest from title-only curiosity."
  ],
  "implementation_angle": [
    "Implementation potential scores 69/100; prioritize adaptation paths for internal agent, evaluation, or platform workflows.",
    "No linked repository is present, so expect more translation work before the ideas are production-ready.",
    "Technical depth scores 100/100, so a quick skim should focus on architecture, data, and evaluation sections before full adoption work."
  ],
  "caveat": "No linked implementation is available yet, which raises integration cost and lowers reproducibility confidence.",
  "links": {
    "hugging_face": "https://huggingface.co/papers/2606.32029",
    "arxiv": "https://arxiv.org/abs/2606.32029"
  }
}