Unverified50% confidenceFactExact time
The authors added a required provenance field to each judging agent's output schema, both tested models followed it well, the cost was almost zero, and the output went from 'confident' to 'verifiable'.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/16/2026
First Seen
Valid until: 10/30/2026
Sources
Related Entities
Related Claims
UnverifiedThis article's tests are hands-on records from a single content creator with a limited sample size, subjective evaluation criteria, and conclusions whose robustness requires verification through larger-scale testing.72% similarUnverified作者将语义正确性与输出格式合规性分离开来评分,并认为这是整个实验中最有价值的发现71% similarVerified投机采样通过小型草稿模型生成候选token由大模型并行验证,可在不损失质量前提下将吞吐提升2-3倍71% similarUnverifiedThe author argues that evaluation should cover both the model layer (reasoning, knowledge, coding, instruction following) and the endpoint layer (speed, reliability, cost, and scalability).70% similarUnverifiedThe paper proposes several directions for developing agent trustworthiness evaluation methods, extending trustworthiness assessment from output verification to scrutiny of the cognitive process itself.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1048499API
curl https://kongchang.com/api/v1/knowledge/claims/1048499MCP
get_claim(id=1048499)