Vivek Gupta, Vivek Srikumar, J Neeraja
We lifted 7 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| utahnlp/knowledge_infotabs | canonical | 5 of 7 |
| Function | Status | Where it lives |
|---|---|---|
| category_from_keys | Ran | utahnlp/knowledge_infotabs/scripts/kg_extraction/extract_kg.py code served (permissive licence) · get_code("f1eba1b799b61e7c") |
| compute_alignment_vector | Ran | utahnlp/knowledge_infotabs/scripts/preprocess/drr.py code served (permissive licence) · get_code("209c9374be821542") |
| is_date | Ran | utahnlp/knowledge_infotabs/scripts/preprocess/bpr.py code served (permissive licence) · get_code("682529bf0fda02fd") |
| sent_Emb | Ran | utahnlp/knowledge_infotabs/scripts/preprocess/drr.py code served (permissive licence) · get_code("ee66d9592ac77597") |
| template | Ran | utahnlp/knowledge_infotabs/scripts/kg_extraction/extract_kg.py code served (permissive licence) · get_code("3f5f061a6f930831") |
| Preprocess_QA_sentences | Not yet run | utahnlp/knowledge_infotabs/scripts/preprocess/drr.py code served (permissive licence) · get_code("4f609f1d33e00926") |
| table_to_para | Not yet run | utahnlp/knowledge_infotabs/scripts/preprocess/bpr.py code served (permissive licence) · get_code("8df7faae1ab29442") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Reasoning about tabular information presents unique challenges to modern NLP approaches which largely rely on pre-trained contextualized embeddings of text. In this paper, we study these challenges through the problem of tabular natural language inference. We propose easy and effective modifications to how information is presented to a model for this task. We show via systematic experiments that these strategies substantially improve tabular inference performance.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2104.04243")
get_code_for_paper("2104.04243")
have("2104.04243")
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