Summary of Researcharena: Benchmarking Large Language Models’ Ability to Collect and Organize Information As Research Agents, by Hao Kang et al.
ResearchArena: Benchmarking Large Language Models’ Ability to Collect and Organize Information as Research Agents
by Hao Kang, Chenyan Xiong
First submitted to arxiv on: 13 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Information Retrieval (cs.IR)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A study introduces ResearchArena, a benchmark designed to evaluate large language models’ capabilities in conducting academic surveys. The process is modeled in three stages: information discovery (identifying relevant literature), information selection (evaluating papers’ relevance and impact), and information organization (structuring knowledge into hierarchical frameworks). Notably, mind-map construction is treated as a bonus task, reflecting its supplementary role in survey-writing. To support these evaluations, the study constructs an offline environment of 12M full-text academic papers and 7.9K survey papers. Preliminary evaluations reveal that LLM-based approaches underperform compared to simpler keyword-based retrieval methods. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary ResearchArena is a new way to test how well computers can help with research tasks like finding and organizing information. The task is broken into three parts: finding relevant articles, deciding which ones are most important, and organizing the knowledge into useful frameworks. One part of this process is making mind maps, but that’s not as important as the other steps. To make it possible to test computers’ abilities, researchers created a huge database with 12 million academic papers and 7,900 survey papers. This will help them figure out how well computer programs can do these tasks compared to humans. |