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Mohammadtaher Safarzadeh

ACL 2026×2评测与基准多模态社会与人本可解释性对齐与偏好
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1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/4ACL 2026Poster· Natural Language Processing

When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias

Xiaohan Zou · Roshan Sridhar · Mohammadtaher Safarzadeh · Dan Roth

摘要

The reliability of VLM-as-a-Judge is critical for the automatic evaluation of vision-language models (VLMs). Despite recent progress, our analysis reveals that VLM-as-a-Judge often pays limited attention to the image when making decisions. Instead, they often blindly favor the more informative an...

多模态评测与基准社会与人本OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

SPENCE : A Syntactic Probe for Detecting Contamination in NL 2 SQL Benchmarks

Mohammadtaher Safarzadeh · Hitesh Laxmichand Patel · Afshin Oroojlooy · Graham Horwood · Dan Roth

摘要

Large language models (LLMs) have achieved strong performance on natural language to SQL (NL2SQL) benchmarks, yet their reported accuracy may be inflated by contamination from benchmark queries or structurally similar patterns seen during training. We introduce SPENCE (Syntactic Probing and Evalu...

评测与基准可解释性对齐与偏好OpenReview 项目页

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