Lost in the Middle
A documented pattern in long context language model behavior where information placed near the start or end of a long input is retrieved more reliably than information buried in the middle of that same input, cited in Section 4 as the mechanism behind why a single sprawling conversation is a less reliable record than a short, isolated saved file (Liu et al., 2023).
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in Agentic AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A documented pattern in long context language model behavior where information placed near the start or end of a long input is retrieved more reliably than information buried in the middle of that same input, cited in Section 4 as the mechanism behind why a single sprawling conversation is a less reliable record than a short, isolated saved file (Liu et al., 2023).
The documented tendency of a model to recall information at the start and end of a long input more reliably than information buried in the middle. A large context window does not guarantee even recall across all of it.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- How AI Actually Works: Algorithms, Data, and Training · AI Fundamentals, AI Literacy & Professional Conduct
- Your AI Briefcase · Taking the Controls, Agentic AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.