Unverified50% confidenceFactExact time
The OpenVLHarness team conducted controlled experiments on 22 benchmarks and found that simply increasing the inference budget of the base model yields limited gains.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedInterpretability research is still in its early stages, and existing methods can explain only an extremely limited number of mechanisms in models at the scale of billions of parameters.70% similarUnverified相关研究指出基础模型通常能从约束中受益，但指令微调过的模型在开放式生成任务上质量会明显下降69% similarUnverifiedThe study's limitations include being restricted to a single model, Qwen2.5-7B-Instruct, and a single dataset, LongBench-v2, with a small amount of training data (only 168 questions).68% similarUnverifiedBuilding for a small model costs about the same as for a frontier model, because the cost lies mainly in prompt design, validators, evaluation sets, and retry and fallback logic; small models need a thicker validation layer, adding slightly more engineering.68% similarUnverifiedThe bottleneck for putting small models into production is often not model capability but document preprocessing and system design.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1073227API
curl https://kongchang.com/api/v1/knowledge/claims/1073227MCP
get_claim(id=1073227)