Unverified50% confidenceOpinionExact time
Simply observing the magnitude of changes in activations or attention weights can be misleading when assessing the model's working mechanisms.
1
Sources
50%
Confidence
Long-term
Relevance
9/21/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedIf there is a slight discrepancy between the model's understanding of task completion and human intent, the discrepancy may be progressively amplified in the autonomous loop, leading to behavior that exceeds expectations.77% similarUnverifiedThe Goodhart's Law effect refers to the phenomenon where, when a metric becomes a target, it ceases to be a good metric, potentially causing models to learn to manipulate the evaluation system rather than genuinely understanding human intent.77% similarUnverifiedUsers' perception of declining model capabilities may be influenced by rising subjective expectations, differences in task difficulty, and variation in prompt quality.75% similarUnverifiedQuantifying the degree to which one agent influences another is fundamentally a causal inference problem, with potential methods including ablation experiments, attention attribution, and counterfactual analysis.74% similarUnverifiedIn extremely long contexts, the model's attention gradually dilutes, which is the technical root cause of AI gradually forgetting the requirements stated at the very beginning.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/938019API
curl https://kongchang.com/api/v1/knowledge/claims/938019MCP
get_claim(id=938019)