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Viktor Schlegel

ACL 2026×2评测与基准可解释性数据与预训练安全检索与知识
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/6ACL 2026Poster· Natural Language Processing

Arg- LL a DA : Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement

Hao Li · Yizheng Sun · Viktor Schlegel · Kailai Yang · Riza Batista-Navarro · Goran Nenadic

摘要

Argument summarization aims to generate concise, structured representations of complex, multi-perspective debates. While recent work has advanced the identification and clustering of argumentative components, the generation stage remains underexplored. Existing approaches typically rely on single...

评测与基准可解释性数据与预训练OpenReview 项目页
作者位次 #2/3ACL 2026Findings· Findings of ACL

Beyond Static Synthetic Noise: Assessing the Robustness of Large Language Models to Natural Context Variation in the Real World

Yulong Wu · Viktor Schlegel · Riza Batista-Navarro

摘要

Robustness evaluation in Question Answering (QA) has predominantly relied on synthetic perturbations that poorly capture natural text evolution in real-world settings, a limitation that becomes more pronounced with the widespread deployment of Large Language Models (LLMs) in dynamic, user-facing...

安全评测与基准检索与知识OpenReview 项目页

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