We lifted 1 functions out of this paper's own repositories and ran 1 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 |
|---|---|---|
| NLPrinceton/SARC | canonical | 1 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| load_sarc_responses | Ran | NLPrinceton/SARC/utils.py code served (permissive licence) · get_code("c3ddefbcc6adaf75") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection. The corpus has 1.3 million sarcastic statements -- 10 times more than any previous dataset -- and many times more instances of non-sarcastic statements, allowing for learning in both balanced and unbalanced label regimes. Each statement is furthermore self-annotated -- sarcasm is labeled by the author, not an independent annotator -- and provided with user, topic, and conversation context. We evaluate the corpus for accuracy, construct benchmarks for sarcasm detection, and evaluate baseline methods.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1704.05579")
get_code_for_paper("1704.05579")
have("1704.05579")
Connect an agent — have() is free.