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Related Questions
- What are some of the key differences in task design that might account for Qwen's reduced performance?
- In what ways does Qwen's reported lower performance relate to its ability to retain state and contextual information during long reasoning tasks?
- How do recent multi-step reasoning benchmarks emphasize domain knowledge and reasoning mechanisms unique to Qwen or models like it?
- Can you illustrate cases where Qwen excelled in multi-step tasks beyond the limitations reported by you?
- Research has shown that increased exposure to training data tends to improve model performance over many reasoning tasks. Why this may not be relevant given Qwen's existing baseline?
- As the Qwen design team investigates further, to improve multi-step reasoning and domain-specific knowledge, should alternative methods or strategies take more prominent roles?
- To better account for reduced performance in multi-step applications, how can human validation or additional training iterations via user feedback improve upon previous testing methods?
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