Papers by Aida Sanatizadeh
Generalization or Memorization? Multi-Agent vs. Baseline LLMs and AutoML Models for Tabular Classification (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) are increasingly used for structured tabular data. |
| Approach: | They evaluate a representative modular Multi-Agent LLM framework against state-of-the-art AutoML systems and established baselines. |
| Outcome: | The proposed model outperforms AutoML on pre-cutoff and post-cut off datasets. |