← Back to all news
arXiv Computation and Language September 17, 2026 By Zimu Xu

Long-Lived Characters, Local Inference: Incremental Memory Maintenance for Game NPCs

Read the original on arXiv Computation and Language →

The Flow has not summarised this story yet — read it at arXiv Computation and Language.

  • efficiency

One email a morning, machine-written

One email a day, machine-written, one click to leave. We never share your address.

Related stories

Hugging Face Trending Papers
Sep 16

Long-Lived Characters, Local Inference: Incremental Memory Maintenance for Game NPCs

A game character should not have to reread its entire life before every conversation. For locally deployed language-model characters, however, revising a few memories can invalidate a long reusable pr...

efficiency
More like this →
arXiv Machine Learning
Aug 7

QEvict: Recoverable Quantized KV Eviction for Attention-Drift-Robust Long-Context Decoding

arXiv:2608. 05326v1 Announce Type: new Abstract: Autoregressive large language model inference is increasingly constrained by the memory footprint of the Key-Value (KV) cache.

By Ayushman Garg, Akshita Gupta, Shaswata Bhattacharya, Abhishek Gupta, Sandeep Kumar, Manoj Kumar
llmsefficiencybenchmarks
More like this →
arXiv AI
Jul 15

MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations

arXiv:2607. 12893v1 Announce Type: new Abstract: Long-term memory has become a foundational capability for LLM-based agents that accompany users across extended, multi-session interactions.

By Xixuan Hao, Zeyu Zhang, Zehao Lin, Yihang Sun, Ziliang Guo, Xichong Zhang, Yuxuan Liang, Feiyu Xiong, Zhiyu Li
llmsagentsnlpbenchmarks
More like this →
arXiv Machine Learning
Aug 4

LiveMem: Maintaining Memory State Continuity in Long-Running LLM Inference

arXiv:2608. 02515v1 Announce Type: cross Abstract: Long-running assistants and agents consume interaction streams that eventually outgrow the context.

By Zhichen Liu, Ruihan Sun, Hengjie Yang, Zipeng Wu, Zhaohan Chen, Xiaofan Zhang, Yang Xu
llmsagentsnlp
More like this →
arXiv AI
Aug 5

LeanMem: Simple and Efficient Long-Term Memory for LLM Agents

arXiv:2608. 03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history.

By Yuxin Liao, Le Wu, Min Hou, Hao Liu, Han Wu, Zishu Wang
llmsagentsnlp
More like this →
arXiv Machine Learning
Jun 30

Memory-Managed Long-Context Attention: A Preliminary Study of Editable Request-Local Memory

arXiv:2606. 28876v1 Announce Type: cross Abstract: Long-context language models often conflate two different goals: compressing history into an efficient state, and maintaining reliable long-term memory.

By Junyi Zou, Avrova Donz
llmsbenchmarks
More like this →
About Pricing API Newsletter Sources Privacy Terms Refunds Accessibility Provider info Contact RSS

The Flow links to publishers and never republishes their articles. Summaries are machine-generated.

v1.1.0 · 5f852ea