新闻
BDH-CQ: In-Context Learning with Recurrent Latent Reasoning
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- BDH-CQ is a reasoning model combining in-context learning with recurrent latent reasoning, achieving 29.5% pass rate on ARC-AGI-1 at $0.0007 per task.
- 为何重要
- Matters for engineers optimizing cost-accuracy tradeoffs in reasoning tasks and evaluating inference efficiency on abstract reasoning benchmarks.
- 注意
- Results are on a single benchmark; generalization to other reasoning tasks and real-world applicability remain unclear from this abstract.
收听本摘要
- reasoning
- inference
- eval
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