Unverified50% confidenceFactExact time
Few-shot prompting failed to close the gap in routing accuracy between generative LLMs and the logistic regression baseline.
1
Sources
50%
Confidence
Long-term
Relevance
10/26/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedMulti-turn self-correction prompting without feedback cannot reliably improve LLM reasoning performance.76% similarVerifiedThe fundamental reason prompt injection is difficult to defend against is that LLMs cannot reliably distinguish between data and instructions.74% similarUnverifiedMethods such as fuzzing, static analysis, and LLM-as-verifier struggle to cover all possible edge cases.73% similarUnverifiedTraditional accuracy metrics fail to capture the internal logical contradictions of LLMs, making it necessary to introduce new evaluation standards such as the information processing gap.72% similarUnverifiedSimply connecting a simulator behind an LLM is not enough; the key lies in how tests are generated and how feedback is utilized.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1098472API
curl https://kongchang.com/api/v1/knowledge/claims/1098472MCP
get_claim(id=1098472)