Purificação Silvano, Ricardo Campos, Alípio Jorge, Inês Cantante, Nuno Guimarães, Miguel Marques, Ana Fernandes, Ana Pacheco, Rute Rebouças, José Isidro, Luís Cunha, Sérgio Nunes, and 1 more
We lifted 7 functions out of this paper's own repositories and ran 0 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 |
|---|---|---|
| INESCTEC/citilink-summ | canonical | 0 of 7 |
| Function | Status | Where it lives |
|---|---|---|
| chunk_text | Not yet run | INESCTEC/citilink-summ/baselines/evaluation/Baseline_Eval_Encoder-Decoder-Models.py pointer only (licence: NONE) · get_code("4122fee46662f7b5") |
| load_citilink | Not yet run | INESCTEC/citilink-summ/baselines/generate_summaries/Baseline_Gen_Encoder-Decoder-Models.py pointer only (licence: NONE) · get_code("c48d31b054aa3243") |
| load_citilink | Not yet run | INESCTEC/citilink-summ/baselines/train_models/Baseline_train_BART.py pointer only (licence: NONE) · get_code("c83b53d1f164c6ef") |
| load_citilink | Not yet run | INESCTEC/citilink-summ/baselines/train_models/Baseline_train_LED.py pointer only (licence: NONE) · get_code("535afe8096e7f1d0") |
| load_generated_data | Not yet run | INESCTEC/citilink-summ/baselines/evaluation/Baseline_Eval_Gemini.py pointer only (licence: NONE) · get_code("54e1a1be2695a377") |
| load_generated_data | Not yet run | INESCTEC/citilink-summ/baselines/evaluation/Baseline_Eval_Qwen.py pointer only (licence: NONE) · get_code("0a4f95db333eaa82") |
| load_test_segments | Not yet run | INESCTEC/citilink-summ/baselines/generate_summaries/Baseline_Gen_Gemini.py pointer only (licence: NONE) · get_code("ccc8f77c3f43e7f2") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Municipal meeting minutes are formal records documenting the discussions and decisions of local government, yet their content is often lengthy, dense, and difficult for citizens to navigate. Automatic summarization can help address this challenge by producing concise summaries for each discussion subject. Despite its potential, research on summarizing discussion subjects in municipal meeting minutes remains largely unexplored, especially in low-resource languages, where the inherent complexity of these documents adds further challenges. A major bottleneck is the scarcity of datasets * Corresponding author.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2602.16607")
get_code_for_paper("2602.16607")
have("2602.16607")
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