Unverified50% confidenceFactExact time
The paper studies two perspectives on observation scaling: predicting a VLM's relative performance as an agent from its public capabilities, and predicting subsequent progress from early physical feedback.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedModels tend to focus on the beginning (Primacy Effect) and end (Recency Effect) of the context, exhibiting a U-shaped attention curve.67% similarUnverifiedHnS measures attribution by observing changes in model behavior rather than relying on gradients or activations from the model's internal parameters; the greater the output change, the greater that concept's contribution to the model's decision.67% similarUnverifiedThe paper's analytical framework is based on leave-one-out cross-validation (LOOCV), and derives the expected out-of-sample performance for OLS and ridge regression separately.67% similarUnverified前沿模型的认定更多依赖于能力评估基准（如MMLU、HumanEval、MATH）的综合表现，而非单纯参数规模67% similarUnverifiedThe study found that even when prompts explicitly instruct the model to answer from a prospective perspective, the model is still influenced by outcome information already present in the context, and physical truncation is the effective means of blocking hindsight bias.66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1073384API
curl https://kongchang.com/api/v1/knowledge/claims/1073384MCP
get_claim(id=1073384)