Arman Cohan, Kyle Lo, Daniel Weld, Isabel Cachola
We lifted 19 functions out of this paper's own repositories and ran 17 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 |
|---|---|---|
| allenai/scitldr | canonical | 5 of 5 |
| bnitsan/papertweet | — | 9 of 10 |
| jungokasai/twist_decoding | — | 3 of 4 |
| Function | Status | Where it lives |
|---|---|---|
| CustomDataset | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("c1e87177e1879e25") |
| add_ctrl | Ran | allenai/scitldr/SciTLDR-Data/build_ctrl_datasets.py code served (permissive licence) · get_code("34369269378d0047") |
| add_eos_token_to_target | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("5a617f87118cdcb7") |
| add_prompt_to_source | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("a6e6d89d8756add2") |
| build_batches | Ran | allenai/scitldr/SciTLDR-Data/to_stories.py code served (permissive licence) · get_code("c62c9d8fca3d91e9") |
| get_line_ids | Ran | jungokasai/twist_decoding/fairseq/twist/generate_twist_tldr.py pointer only (licence: NONE) · get_code("4f101059eeab11c8") |
| get_num_train_steps | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("39d9cd45b8edce68") |
| get_train_dataloaders | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("cb94a51b64280335") |
| get_url_hashes | Ran | allenai/scitldr/SciTLDR-Data/make_datafiles.py code served (permissive licence) · get_code("478f0055455e2023") |
| get_val_dataloaders | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("238977a0b4ed33b4") |
| hashhex | Ran | allenai/scitldr/SciTLDR-Data/make_datafiles.py code served (permissive licence) · get_code("2ed659a3dd835939") |
| jaccard | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("18e9681c72c82d0d") |
| pad_candidates | Ran | jungokasai/twist_decoding/fairseq/twist/generate_twist_tldr.py pointer only (licence: NONE) · get_code("258d4a4b0a8b6b16") |
| read_input | Ran | jungokasai/twist_decoding/fairseq/twist/generate_twist_tldr.py pointer only (licence: NONE) · get_code("53d5b85264377a72") |
| read_text_file | Ran | allenai/scitldr/SciTLDR-Data/make_datafiles.py code served (permissive licence) · get_code("8175760b8eddec2b") |
| rouge_score | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("9447eeb9dbba8819") |
| train_val_test_path | Ran | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("f6ceffd4a0becc2a") |
| CondGenModel | Not yet run | bnitsan/papertweet/models/model.py code served (permissive licence) · get_code("0e0ae26c9368468f") |
| generate_TLDRs | Not yet run | jungokasai/twist_decoding/fairseq/twist/generate_twist_tldr.py pointer only (licence: NONE) · get_code("bba331b9f86f6008") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study on this task, we introduce SCITLDR, a new multi-target dataset of 5.4K TLDRs over 3.2K papers. SCITLDR contains both author-written and expert-derived TLDRs, where the latter are collected using a novel annotation protocol that produces high-quality summaries while minimizing annotation burden. We propose CATTS, a simple yet effective learning strategy for generating TLDRs that exploits titles as an auxiliary training signal. CATTS improves upon strong baselines under both automated metrics and human evaluations. Data and code are publicly available at https://github.com/allenai/scitldr. 1 TLDR is an acronym that stands for "too long; didn't read," which is often used in online informal discussion (e.g., Twitter or Reddit) about scientific papers. For visual clarity, we omit the semi-colon.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2004.15011")
get_code_for_paper("2004.15011")
have("2004.15011")
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