daily-paper-generator

Automating arXiv EEG paper discovery involves searching recent publications, extracting metadata, and generating structured bilingual Chinese-English summaries. This Skill identifies recent EEG decoding and brain-computer interface papers within the last 3 months and produces structured abstracts saved under timestamped filenames.

Finding recent EEG foundation model papers requires automated search and quality assessment of arXiv publications. This Skill evaluates near-term papers against specific quality criteria, generating bilingual reviews and structured metadata to accelerate your literature review workflow.

Generating Chinese-English summaries for brain-computer interface papers is supported by applying automated quality assessment and structured templates. The output produces bilingual reviews and structured abstracts per paper, aligned with predefined example formats for publishing or sharing.

The daily paper generator requires the feedparser dependency to search arXiv for recent EEG papers. It uses this library to automate the identification and metadata extraction of near-term publications in EEG decoding, brain-computer interfaces, and foundation models from the last 3 months.

Evaluating the quality of recent EEG decoding papers applies specific quality criteria to filter arXiv search results. The Skill assesses identified publications against defined standards and generates structured bilingual reviews satisfying these requirements for your research workflow.

Limitations when automating bilingual summaries for EEG daily paper tracking include the strict 3-month publication window for arXiv papers. The automated search and quality assessment specifically target EEG decoding, brain-computer interfaces, and foundation models, excluding older archives or other neuroscience domains.