Unverified50% confidenceOpinionExact time
WOVEN's argument essentially attributes part of MLLMs' deficiencies to a lack of world model capability—that is, although the model can describe image content, it cannot simulate how it evolves with actions.
1
Sources
50%
Confidence
Long-term
Relevance
10/13/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedUllman等人指出模型在错误信念任务经过微小变体修改后便大幅失准，暗示其依赖表面模式而非真正的心智建模72% similarUnverifiedA perfect score may indicate that the set of questions has lost its ability to differentiate between models.72% similarVerifiedWhen the model itself lacks the capability to understand a specific problem, no amount of prompt engineering can compensate for this deficiency70% similarUnverifiedAcademia typically uses benchmarks such as MMLU and HumanEval to quantify model capability degradation.70% similarUnverifiedFew-shot failure does not necessarily mean that examples interfered with the model; it may also be that the model did not produce sufficient representational reconstruction of the example content.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1013390API
curl https://kongchang.com/api/v1/knowledge/claims/1013390MCP
get_claim(id=1013390)