Papers by Yaoyu Zhou

2 papers
CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering (2026.findings-acl)

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Challenge: Large language models (LLMs) possess strong capabilities in language understanding and generation, as well as remarkable problem-solving abilities.
Approach: They propose a benchmark to assess the cognitive alignment capabilities of large language models in educational QA.
Outcome: The proposed evaluation benchmark assesses the cognitive alignment capabilities of large language models in educational QA.
Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism (2025.findings-emnlp)

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Challenge: Large language models struggle with complex reasoning tasks, such as mathematical problem-solving.
Approach: They constructed a symbolic multi-step reasoning task to investigate the information propagation mechanisms in Transformer models when solving the task through direct answering and Chain-of-Thought (CoT) reasoning.
Outcome: The proposed algorithm improves on 7 multi-step reasoning datasets, while introducing only 132 trainable parameters.

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