Verified65% confidenceFactExact time
Greedy decoding selects the token with the highest current probability at every step, which tends to accumulate systematic bias in multi-step tasks because local optima do not equal global optima.
3
Sources
65%
Confidence
Long-term
Relevance
7/18/2026
First Seen
Sources
Related Claims
UnverifiedGreedy decoding always selects the token with the highest probability, while random sampling draws from the probability distribution, which means the same prompt may yield different responses.78% similarUnverifiedWriting to more positions in parallel speeds up inference but also increases the risk of deviating from the true distribution, constituting a trade-off between speed and fidelity.74% similarUnverifiedWhen prior knowledge about possible fault patterns is available, selecting a sparse penalty structure that matches them often yields significant performance gains over general-purpose algorithms73% similarUnverifiedIn grounded modes, reranking is almost mandatory, because the risk of incorrect retrieval far outweighs the cost of additional latency.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/550211API
curl https://kongchang.com/api/v1/knowledge/claims/550211MCP
get_claim(id=550211)