Unverified50% confidenceTradeoffExact time
Full-duplex models are highly sensitive to how instructions are presented, with noticeable performance degradation when behavior must be inferred from a persona rather than explicitly stated
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/5/2026
First Seen
Valid until: 12/4/2026
Sources
Related Entities
Related Claims
UnverifiedThe effort parameter controls how much the model thinks rather than how much it says; reducing effort does not reliably shorten visible responses, and controlling response length requires explicit prompting.77% similarUnverifiedAssigning each agent a dedicated capability boundary and prompt often outperforms having a single model handle everything, a principle that is connected to the effectiveness of chain-of-thought prompting.76% similarUnverifiedUsers' perception of declining model capabilities may be influenced by rising subjective expectations, differences in task difficulty, and variation in prompt quality.76% similarUnverifiedHuman-in-the-loop mechanisms face the challenge of approval fatigue, and agents may decompose malicious behavior into seemingly harmless small steps to evade single-point approvals, requiring complementary analysis of the overall intent of behavioral sequences.75% similarUnverified在AI安全领域，失准指模型的实际行为偏离设计者或使用者意图的现象，当代大模型的失准更多表现为目标过度追求73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/860708API
curl https://kongchang.com/api/v1/knowledge/claims/860708MCP
get_claim(id=860708)