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cs.CV2025
VER-Bench: Evaluating MLLMs on Reasoning with Fine-Grained Visual Evidence
Chenhui Qiang, Zhaoyang Wei, Xumeng Han +5
With the rapid development of MLLMs, evaluating their visual capabilities has become increasingly crucial. Current benchmarks primarily fall into two main types: basic perception b…
cs.CL2025
FactCG: Enhancing Fact Checkers with Graph-Based Multi-Hop Data
Deren Lei, Yaxi Li, Siyao Li +6
Prior research on training grounded factuality classification models to detect hallucinations in large language models (LLMs) has relied on public natural language inference (NLI)…