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Daixuan Li

2 accepted papers

2025

Invoke Interfaces Only When Needed: Adaptive Invocation for Large Language Models in Question Answering

EMNLP 2025

The collaborative paradigm of large and small language models (LMs) effectively balances performance and cost, yet its pivotal challenge lies in precisely pinpointing the moment of invocation when hallucinations arise in small LMs. Previous optimization efforts primarily focused on post-processing t

2025

Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs

NeurIPS 2025poster

Modern engineering, spanning electrical, mechanical, aerospace, civil, and computer disciplines, stands as a cornerstone of human civilization and the foundation of our society. However, engineering design poses a fundamentally different challenge for large language models (LLMs) compared with tradi…

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