Nanyun Peng, Smaranda Muresan, Tuhin Chakrabarty, Debanjan Ghosh
We lifted 9 functions out of this paper's own repositories and ran 6 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 |
|---|---|---|
| ying09/TextFuseNet | pwc_unofficial | 6 of 9 |
| Function | Status | Where it lives |
|---|---|---|
| batched_nms | Ran | ying09/TextFuseNet/detectron2/layers/nms.py code served (permissive licence) · get_code("0df9d3b583fbc6cb") |
| compute_polygon_area | Ran | ying09/TextFuseNet/demo/ctw1500_detection.py code served (permissive licence) · get_code("dd81247228bb9b05") |
| convert_basic_c2_names | Ran | ying09/TextFuseNet/detectron2/checkpoint/c2_model_loading.py code served (permissive licence) · get_code("e8526a516b4f9206") |
| convert_c2_detectron_names | Ran | ying09/TextFuseNet/detectron2/checkpoint/c2_model_loading.py code served (permissive licence) · get_code("52810b504f0d1066") |
| pad_masks | Ran | ying09/TextFuseNet/detectron2/layers/mask_ops.py code served (permissive licence) · get_code("406f84cf799ed34d") |
| paste_mask_in_image_old | Ran | ying09/TextFuseNet/detectron2/layers/mask_ops.py code served (permissive licence) · get_code("d03592674030077f") |
| batched_nms_rotated | Not yet run | ying09/TextFuseNet/detectron2/layers/nms.py code served (permissive licence) · get_code("4845964b76bba6c5") |
| nms_rotated | Not yet run | ying09/TextFuseNet/detectron2/layers/nms.py code served (permissive licence) · get_code("d3fa37a000ad294d") |
| paste_masks_in_image | Not yet run | ying09/TextFuseNet/detectron2/layers/mask_ops.py code served (permissive licence) · get_code("f74abd7e1355f8cd") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We propose an unsupervised approach for sarcasm generation based on a non-sarcastic input sentence. Our method employs a retrieve-andedit framework to instantiate two major characteristics of sarcasm: reversal of valence and semantic incongruity with the context, which could include shared commonsense or world knowledge between the speaker and the listener. While prior works on sarcasm generation predominantly focus on context incongruity, we show that combining valence reversal and semantic incongruity based on commonsense knowledge generates sarcastic messages of higher quality based on several criteria. Human evaluation shows that our system generates sarcasm better than human judges 34% of the time, and better than a reinforced hybrid baseline 90% of the time.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2004.13248")
get_code_for_paper("2004.13248")
have("2004.13248")
Connect an agent — have() is free.