Review Generation
17 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Review Generation
Most implemented papers
Can We Automate Scientific Reviewing?
The rapid development of science and technology has been accompanied by an exponential growth in peer-reviewed scientific publications.
Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach
We distill several insights from our analysis on study the peer review process with the help of large LMs.
Hierarchical Catalogue Generation for Literature Review: A Benchmark
Scientific literature review generation aims to extract and organize important information from an abundant collection of reference papers and produces corresponding reviews while lacking a clear and logical hierarchy.
Summarizing Multiple Documents with Conversational Structure for Meta-Review Generation
We present PeerSum, a novel dataset for generating meta-reviews of scientific papers.
SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generation
Automatic literature review generation is one of the most challenging tasks in natural language processing.
Scientific Opinion Summarization: Meta-review Generation with Checklist-guided Iterative Introspection
Opinions in the scientific domain can be divergent, leading to controversy or consensus among reviewers.
MARG: Multi-Agent Review Generation for Scientific Papers
We study the ability of LLMs to generate feedback for scientific papers and develop MARG, a feedback generation approach using multiple LLM instances that engage in internal discussion.