Unverified50% confidenceOpinionExact time
Speech scientists or computational linguists are the first to identify data quality issues when training models, but do not necessarily hold purchasing authority.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSome critics argue that the scale of training data is the key factor determining AI generation quality, and that language simplicity may not be the decisive factor.73% similarUnverified在机器人学习研究中,训练失败时研究者通常首先怀疑模型架构或超参数选择,而数据质量问题往往是最后才被排查到的因素69% similarUnverifiedThe capability of supervised learning models is bounded by the ceiling of data quality and cannot surpass the level of the teacher algorithm.67% similarVerifiedBenchmark leaderboards measure a model's test-taking ability rather than its ability to solve real problems67% similarUnverifiedAutoregressive language models have never seen 'I don't know' as a high-frequency reasonable output during training, so they are more likely to generate fabricated content at the boundaries of their knowledge than to express uncertainty66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/905301API
curl https://kongchang.com/api/v1/knowledge/claims/905301MCP
get_claim(id=905301)