Problem
Research questions and friction points this paper is trying to address.
scientific publishing
paper overload
research insight
trending papers
information overload
Paper Espresso: From Paper Overload to Research Insight
🤖 AI Summary
This work addresses the challenge of tracking rapidly evolving research trends amid the exponential growth of academic publications by introducing an open-source platform that leverages large language models (LLMs) to automatically process high-impact arXiv papers. The system employs LLM-driven thematic clustering and generates structured summaries enriched with tags and keywords, enabling trend analysis at daily, weekly, and monthly granularities. Over 35 consecutive months, it processed more than 13,300 papers, uncovering key dynamics such as the surge of reinforcement learning in LLM reasoning and the emergence of non-saturated research topics. The analysis further reveals a significant positive correlation between paper novelty and community engagement, with the most innovative works receiving twice the median number of likes. All metadata are publicly released, and the system is available as an online demo.
📝 Abstract
The accelerating pace of scientific publishing makes it increasingly difficult for researchers to stay current. We present Paper Espresso, an open-source platform that automatically discovers, summarizes, and analyzes trending arXiv papers. The system uses large language models (LLMs) to generate structured summaries with topical labels and keywords, and provides multi-granularity trend analysis at daily, weekly, and monthly scales through LLM-driven topic consolidation. Over 35 months of continuous deployment, Paper Espresso has processed over 13,300 papers and publicly released all structured metadata, revealing rich dynamics in the AI research landscape: a mid-2025 surge in reinforcement learning for LLM reasoning, non-saturating topic emergence (6,673 unique topics), and a positive correlation between topic novelty and community engagement (2.0x median upvotes for the most novel papers). A live demo is available at https://huggingface.co/spaces/Elfsong/Paper_Espresso.
Innovation
Methods, ideas, or system contributions that make the work stand out.
large language models
trend analysis
structured summarization
topic consolidation
research landscape
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