Chris Biemann, Tim Fischer
We lifted 6 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 |
|---|---|---|
| uhh-lt/dats | canonical | 0 of 6 |
| Function | Status | Where it lives |
|---|---|---|
| base64_to_image | Not yet run | uhh-lt/dats/ray/src/utils.py code served (permissive licence) · get_code("55c5912c92a2f176") |
| bytes_to_wav_data | Not yet run | uhh-lt/dats/ray/src/utils.py code served (permissive licence) · get_code("3befdf39d242906f") |
| check_no_modules_import | Not yet run | uhh-lt/dats/backend/lint/check_core.py code served (permissive licence) · get_code("68dc21dc7f275d4d") |
| get_all_apps | Not yet run | uhh-lt/dats/ray/src/generate_specs.py code served (permissive licence) · get_code("b0be524e6008086b") |
| image_to_base64 | Not yet run | uhh-lt/dats/ray/src/utils.py code served (permissive licence) · get_code("239b63a91ca3d84b") |
| run_build_cmd | Not yet run | uhh-lt/dats/ray/src/generate_specs.py code served (permissive licence) · get_code("be71df14bdddfa22") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
This paper introduces Perspectives, an interactive extension of the Discourse Analysis Tool Suite designed to empower Digital Humanities (DH) scholars to explore and organize large, unstructured document collections. Perspectives implements a flexible, aspect-focused document clustering pipeline with human-in-theloop refinement capabilities. We showcase how this process can be initially steered by defining analytical lenses through document rewriting prompts and instruction-based embeddings, and further aligned with user intent through tools for refining clusters and mechanisms for fine-tuning the embedding model. The demonstration highlights a typical workflow, illustrating how DH researchers can leverage Perspectives's interactive document map to uncover topics, sentiments, or other relevant categories, thereby gaining insights and preparing their data for subsequent in-depth analysis.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2602.15540")
get_code_for_paper("2602.15540")
have("2602.15540")
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