AgenticSTS: Bounded-Memory Testbed for Long-Horizon LLM Agents
Alaya Studio
Proposes a bounded-memory contract for long-horizon LLM agents: each decision step is built from a fresh message assembled via typed retrieval from separate explicit memory layers (observations, tool calls, reflections). Instantiated in a Slay the Spire 2 testbed with 298 completed trajectories, enabling ablation of individual memory components in isolation.
Why it matters
Existing agents that append full history make it impossible to isolate which memory component drives a decision; this controlled framework enables causal measurement of each memory type, relevant to building agents with predictable memory budgets.
Importance: 2/5
Novel benchmarking methodology with immediate practical relevance to agent memory design.
Sources
official
arXiv:2607.02255 — AgenticSTS
media
HuggingFace Daily Papers