Unverified50% confidenceOpinionExact time
The conversational memory of current mainstream large models is fragmented, with each interaction starting almost from scratch, requiring users to repeatedly provide background information.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe context window determines how much content the model can remember within a single conversation.77% similarUnverifiedAt the start of each session, the user's memory.md is loaded in as context.75% similarVerifiedThe context window mechanism causes models in multi-turn conversations to feed the entire conversation history into the context, causing token consumption to grow rapidly as the conversation lengthens.75% similarVerifiedChat Memory simulates memory by injecting historical messages into the Prompt with each request, causing token consumption to grow linearly with the number of conversation turns.75% similarUnverifiedThe memory layer is responsible for storing, retrieving, and managing information accumulated by an Agent during interactions, enabling it to maintain continuity across sessions.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1010392API
curl https://kongchang.com/api/v1/knowledge/claims/1010392MCP
get_claim(id=1010392)