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Prasanna Sattigeri

ACL 2026×2可解释性效率与系统检索与知识推理对齐与偏好
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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 #4/5ACL 2026Poster· Natural Language Processing

Multi-component Causal Tracing in Large Language Models

Zirui Yan · Dennis Wei · Dmitriy A Katz · Prasanna Sattigeri · Ali Tajer

摘要

Causal tracing systematically intervenes on a large language model’s (LLM’s) internal representations to uncover and quantify the causal pathways linking specific inputs or computations to specific metrics of interest, quantifying the LLM’s behavior. Building on previous single-component or singl...

可解释性效率与系统检索与知识OpenReview 项目页
作者位次 #5/5ACL 2026Poster· Natural Language Processing

Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLM s

Abinitha Gourabathina · Inkit Padhi · Manish Nagireddy · Subhajit Chaudhury · Prasanna Sattigeri

摘要

For Large Language Models (LLMs) to be reliably deployed, models must effectively know when not to answer: abstain. Reasoning models, in particular, have gained attention for impressive performance on complex tasks. However, reasoning models have been shown to have worse abstention abilities. Tak...

推理对齐与偏好安全OpenReview 项目页

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