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PosterMELD is a template-conditioned multi-agent pipeline that converts academic papers into editable, print-ready posters, achieving 81.3% Print-Ready Rate with low cost, and is released with code and resources.
This paper constructs a multimodal dataset of 1000 academic papers with text, images, and audio to study keyword extraction, showing that fusing multiple modalities improves performance.
This study examines how team institutional composition (academic, industrial, or mixed) affects the novelty of academic papers in NLP, using fine-grained knowledge entities like methods and datasets to measure novelty.
This paper investigates prompt-based learning for automatically generating highlights of academic papers, using models like GPT-2, T5, and ChatGPT, and shows that ChatGPT with few-shot prompts achieves performance comparable to or better than supervised methods without requiring task-specific training data.
A local-first academic paper management desktop application linXiv, supporting paper discovery, management, and visualization from sources like arXiv, integrating SQLite database, AI annotation, Obsidian notes, and paper network graph.
The user praised a product launched by Baidu that effectively solves the pain point of dealing with numbers when translating papers, considering it a necessity.
A user announces that Claude can now process dozens of academic papers into structured insights, sharing 9 prompts to leverage this capability.
A podcast episode discusses the growing prevalence of AI hallucinations in academic papers, attributing it to poor working conditions for academics and warning of dangers to future research and knowledge production.