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Subhabrata Dutta

ACL 2026×2对齐与偏好可解释性强化学习与后训练评测与基准推理
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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 #3/4ACL 2026Poster· Natural Language Processing

Patches of Nonlinearity: Instruction Vectors in Large Language Models

Irina Bigoulaeva · Jonas Rohweder · Subhabrata Dutta · Iryna Gurevych

摘要

Despite the recent success of instruction-tuned language models and their ubiquitous usage, very little is known of how models process instructions internally. In this work, we address this gap from a mechanistic point of view by investigating how instruction-specific representations are construc...

可解释性对齐与偏好强化学习与后训练OpenReview 项目页
作者位次 #2/3ACL 2026Poster· Natural Language Processing

Reward Modeling for Scientific Writing Evaluation

Furkan Şahinuç · Subhabrata Dutta · Iryna Gurevych

摘要

Scientific writing is an expert-domain task that demands deep domain knowledge, task-specific requirements and reasoning capabilities that leverage the domain knowledge to satisfy the task specifications. While scientific text generation has been widely studied, its evaluation remains a challengi...

评测与基准对齐与偏好推理OpenReview 项目页

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