ByteDance-Seed / ByteDance-Seed/Bagel
生成是如何促进理解的呢?
Open
- Dominant language
- Python
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- 6.2k
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Description
研究了下meta-query 和 bagel 的工作,已知理解和生成在数学上是对偶任务,理解促进生成的case 很直观,比如:
1. PE 扩写
2. 统一架构下,DIT 的模块可以看到 ARtoken 的信息,去帮助生成
那么生成促进理解,有哪些比较直观的 case 呢?
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reviewing the meta-query and Bagel work referenced in the issue, along with the PE expansion and unified DIT/AR-token examples. Identify intuitive cases where generation could improve understanding, then document the cases and explain how the dual tasks interact. No files or tests are named in the issue.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100