Papers by Clara Lachenmaier

2 papers
Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals distinct Multi-Turn Behavior in LLMs (2026.acl-long)

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Challenge: a lot of research aims to mitigate these problems by introducing specific computational solutions.
Approach: They examine how large language models engage in the interactive process of repair in multi-turn dialogues around solvable and unsolvable math questions.
Outcome: The models respond to user-initiated repair differently from one another . the models exhibit their own characteristic form of unreliability in the context of repair .
Can LLMs Ground when they (Don’t) Know: A Study on Direct and Loaded Political Questions (2025.acl-long)

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Challenge: Using large language models, interlocutors can reach mutual understanding even when they do not possess perfect knowledge.
Approach: They examine whether loaded questions lead LLMs to engage in active grounding and correct false user beliefs in connection to their level of knowledge and their political bias.
Outcome: The proposed model can answer direct knowledge questions and loaded questions that presuppose misinformation, while ignoring false user beliefs.

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