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add one work about table embeddings and one work about table representation #19

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add one work about table embeddings and one work about table representation #19

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7 changes: 7 additions & 0 deletions README.md
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Expand Up @@ -79,6 +79,8 @@ Figure 4: Key techniques in using LLMs for tabular data. The dotted line indicat
**[Towards Foundation Models for Learning on Tabular Data](https://arxiv.org/abs/2310.07338)**


**[Observatory: Characterizing Embeddings of Relational Tables](https://www.vldb.org/pvldb/vol17/p849-cong.pdf)**
**[[code](https://github.com/superctj/observatory)]**


**[Towards Better Serialization of Tabular Data for Few-shot Classification with Large Language Models
Expand Down Expand Up @@ -280,6 +282,11 @@ Knowledge Grounding
**[Disambiguate Entity Matching using Large Language Models through Relation Discovery](https://dl.acm.org/doi/abs/10.1145/3665601.3669844)**
**[[code](https://cocoon-data-transformation.github.io/page/standardize)]**

#### Table Representation

**[Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMs](https://arxiv.org/pdf/2402.12424)**


<a id="dataset"></a>
## Datasets
Please refer to our paper to see relevant methods that benchmark on these datasets.
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