Papers by Guande He

2 papers
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World (2024.findings-acl)

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Challenge: Existing studies on how large language model agents collaborate with humans in equal roles emphasize the importance of coordination and communication.
Approach: They propose to use chain-of-thought prompts to evaluate different collaboration perspectives, from independent to more complex, dependent tasks.
Outcome: The proposed model significantly improves the evaluation metric.
Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models (2025.coling-main)

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Challenge: Multimodal large language models combine visual and textual data for tasks like image captioning and visual question answering.
Approach: They propose temperature scaling and iterative prompt optimization to calibrate MLLMs and enhance model reliability.
Outcome: The proposed techniques improve MLLMs and improve model reliability.

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