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Table serialization format impacts language model data retrieval

A new research paper explores how the way tables are serialized into text impacts language models' ability to retrieve information. The study found that the optimal serialization format (row-major vs. column-major) depends on the table's aspect ratio, with tall tables benefiting from row-major and wide tables from column-major formats. This suggests that language models' failures in text-serialized tables are linked to linearization methods rather than just the table's shape. AI

IMPACT Understanding how data serialization affects LLM performance is crucial for optimizing data preparation and improving model accuracy in real-world applications.

RANK_REASON Research paper published on arXiv detailing findings about language model behavior. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Table serialization format impacts language model data retrieval

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Research paper published on arXiv detailing findings about language model behavior. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Junwei Ma, Arun Kumar Chithanar, Palash Goyal, Chul Lee ·

    Table Serialization Determines Which Relations Language Models Preserve

    arXiv:2610.24798v2 Announce Type: replace Abstract: We study how text serialization affects table lookup in instruction-tuned language models. Our diagnostic asks the model to find the row containing a specified value under one named column, then return the value under another na…