MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations
Long-term memory has become a foundational capability for LLM-based agents that accompany users across extended, multi-session interactions. Existing benchmarks, however, evaluate such memory almost exclusively through downstream question a
https://arxiv.org/abs/2607.12893v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
Light
How close the company’s idea is to your thesis statement
Sector
agents, llm
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
▸ Add / edit details
Correct facts used on the next screening or memo.
People
X
Xixuan Hao
1.0
low confidence
Z
Zeyu Zhang
1.0
low confidence
Z
Zehao Lin
1.0
low confidence
Y
Yihang Sun
1.0
low confidence
Z
Ziliang Guo
1.0
low confidence
X
Xichong Zhang
1.0
low confidence
Y
Yuxuan Liang
1.0
low confidence
F
Feiyu Xiong
1.0
low confidence
Z
Zhiyu Li
1.0
low confidence