Unverified50% confidenceBenchmarkExact time
The paper tested the best pure schema-filtering configuration on the BIRD dataset, and still about 27% of questions that should have been refused were answered by the model.
1
Sources
50%
Confidence
Long-term
Relevance
10/17/2026
First Seen
Sources
Related Entities
Related Claims
Unverified研究显示代码审查中约30%-50%的评审意见与风格和规范相关,而非逻辑错误67% similarUnverifiedschemagate's benchmark results measure whether the correct table entered the prompt, not whether the final SQL is correct; only one model was used; Spider and BIRD are public datasets, and the model may have seen them in training; the reranker only re-ranks tables already selected by the mathematical method, and can only see table names and brief summaries.67% similarUnverifiedTraditional speculative decoding uses strict rejection-sampling-based verification rules, where a draft token is only accepted when it exactly matches the target model's sampled result.66% similarUnverifiedThe evaluation uses an option-order reversal test (26 pairs) to distinguish whether a model truly understands the content or relies on option position to answer.63% similarUnverifiedBuilding a small test set should start with 30 to 50 real questions, each accompanied by the correct answer and the document containing the answer, measuring retrieval (whether the correct text chunk appears in the top results) and generation (whether the final answer is supported by the retrieved text) separately.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1051141API
curl https://kongchang.com/api/v1/knowledge/claims/1051141MCP
get_claim(id=1051141)