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Swanand Ravindra Kadhe

ACL 2026×2NDSS 2026安全可解释性强化学习与后训练对齐与偏好推理
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0 一作 · 3 篇 · ACL 2026 / NDSS 2026

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2026 顶会论文

3
作者位次 #2/5ACL 2026Findings· Findings of ACL

S afe MERGE : Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging

Aladin Djuhera · Swanand Ravindra Kadhe · Farhan Ahmed · Syed Zawad · Holger Boche

摘要

Fine-tuning large language models (LLMs) is a common practice to adapt generalist models to specialized domains. However, recent studies show that fine-tuning can erode safety alignment, causing LLMs to respond to harmful or unethical prompts. Many methods to realign safety have been proposed, bu...

安全对齐与偏好强化学习与后训练OpenReview 项目页
作者位次 #2/5ACL 2026Findings· Findings of ACL

ST a D : Scaffolded Task Design for Identifying Compositional Skill Gaps in LLM s

Sungeun An · Swanand Ravindra Kadhe · Shailja Thakur · Chad DeLuca · Hima Patel

摘要

Benchmarks are often used as a standard to understand LLM capabilities in different domains. However, aggregate benchmark scores provide limited insight into compositional skill gaps of LLMs and how to improve them. To make these weaknesses visible, we propose Scaffolded Task Design (STaD) framew...

推理可解释性评测与基准OpenReview 项目页

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