PRISM benchmark finds LLMs match or exceed humans on isolated review dimensions like novelty verification but none achieve the balanced performance of human reviewers across depth, flaw prioritization, and constructiveness.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Mixed academic-industrial teams in NLP produce more novel papers than purely industrial teams, with mixed teams emphasizing method-metric novelty and industrial teams emphasizing method-tool novelty.
citing papers explorer
-
PRISM: A Multi-Dimensional Benchmark for Evaluating LLM Peer Reviewers
PRISM benchmark finds LLMs match or exceed humans on isolated review dimensions like novelty verification but none achieve the balanced performance of human reviewers across depth, flaw prioritization, and constructiveness.
-
Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities
Mixed academic-industrial teams in NLP produce more novel papers than purely industrial teams, with mixed teams emphasizing method-metric novelty and industrial teams emphasizing method-tool novelty.