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Carolin Lawrence

ACL 2026×2长上下文与架构可解释性强化学习与后训练推理评测与基准
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

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作者位次 #4/5ACL 2026Poster· Natural Language Processing

Compositional Steering of Large Language Models with Steering Tokens

Gorjan Radevski · Kiril Gashteovski · Giwon Hong · Carolin Lawrence · Goran Glavaš

摘要

Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work extensively addresses LLM steering for a single behavior, compositional steering—i.e., steering LLMs simultaneously towards multiple behaviors—remains an...

长上下文与架构可解释性强化学习与后训练OpenReview 项目页
作者位次 #7/11ACL 2026Findings· Findings of ACL

Scaling Evaluation-Time Compute with Reasoning Models as Evaluators

Seungone Kim · Ian Wu · Jinu Lee · Xiang Yue · Seongyun Lee · Minkyeong Moon · Carolin Lawrence · Kiril Gashteovski · Julia Hockenmaier · Graham Neubig · Sean Welleck

摘要

Language model (LM) evaluators that generate chain-of-thought (CoT) reasoning are widely used for the assessment of LM responses. Simultaneously, increasing LMs’ “thinking” time through scaling test-time compute has proven to be an effective technique for solving challenging problems in domains s...

推理评测与基准代码OpenReview 项目页

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