Introduces VURB benchmark and VUP-35K dataset to train discriminative and generative video reward models that achieve SOTA performance on VURB and VideoRewardBench.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
SciHorizon-GENE is a large-scale benchmark evaluating LLMs on gene-to-function inference across four perspectives, revealing heterogeneity and challenges in faithful, complete, literature-grounded outputs.
citing papers explorer
-
Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models
Introduces VURB benchmark and VUP-35K dataset to train discriminative and generative video reward models that achieve SOTA performance on VURB and VideoRewardBench.
-
SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding
SciHorizon-GENE is a large-scale benchmark evaluating LLMs on gene-to-function inference across four perspectives, revealing heterogeneity and challenges in faithful, complete, literature-grounded outputs.