Memory & Continual Learning
Long-context understanding, persistent memory, RAG systems, and lifelong learning. Giving AI the ability to remember and learn continuously.
Key Benchmarks
Recent Papers
AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents
Xiangchen Cheng, Yunwei Jiang, Jianwen Sun +7 more
DuoMem: Towards Capable On-Device Memory Agents via Dual-Space Distillation
Shengguang Wu, Hao Zhu, Yuhui Zhang +2 more
ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation
Zhaoqi Wang, Zijian Zhang, Kun Zheng +4 more
Information-Aware KV Cache Compression for Long Reasoning
Jushi Kai, Zhuiri Xiao, Alexandra Birch +1 more
LedgerAgent: Structured State for Policy-Adherent Tool-Calling Agents
Md Nayem Uddin, Amir Saeidi, Eduardo Blanco +1 more
LedgerAgent: Structured State for Policy-Adherent Tool-Calling Agents
Md Nayem Uddin, Amir Saeidi, Eduardo Blanco +1 more
GRIP: Feedback-Guided Prompt Retrieval for Large Multimodal Models
Garvita Allabadi, Matteo Sodano, Roberto Estevão +4 more
EvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic Environments
Jundong Xu, Qingchuan Li, Jiaying Wu +9 more
Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning
Zilin Xiao, Qi Ma, Chun-cheng Jason Chen +4 more
Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution
Liliana Hotsko, Yinxi Li, Yuntian Deng +1 more
Recent Milestones
EVAF Adds Durable Goals to Long‑Running Agents
On June 25, 2026, a preprint by Haoliang Han introduced EVAF, a gated LoRA-based consolidation mechanism that writes long-term goals into a small parametric store so agents retain behavior even after context is cleared. On June 28, 24 AI’s "Today in AI" digest spotlighted the work as a key advance in persistent memory for long-running language agents. ([arxiv.org](https://arxiv.org/abs/2606.26806?utm_source=openai))
GLM‑5.2: 1M‑Token Open Coding Model
On June 13, 2026, Zhipu AI’s international brand Z.ai rolled out its GLM‑5.2 model to all GLM Coding Plan users, featuring a 1‑million‑token context window and new ‘High’ and ‘Max’ reasoning modes. The company says an API and MIT‑licensed open‑weight release will follow next week, positioning GLM‑5.2 as its most capable open model for long‑horizon coding and agents.
ChatGPT gets scalable long‑term memory
On June 4, 2026, OpenAI detailed a new "dreaming"-based memory system for ChatGPT designed to synthesize and refresh long‑term user memories at scale. The rollout aims to improve how ChatGPT recalls user preferences, projects and context across multi‑year interactions.
NVIDIA Context Memory hits mainstream servers
On May 26, 2026, AIC announced via PRNewswire that it will showcase new AI storage and compute platforms and co-host a ‘Breaking the Memory Wall’ panel with NVIDIA and VAST Data at Computex 2026 in Taipei. The company will demonstrate systems built around NVIDIA’s Context Memory Platform, BlueField-4 and high-density GPU servers aimed at long-context LLMs, video analytics, and agentic AI workloads.
Gemini 1.5 Pro 2M Context
Google expands Gemini 1.5 Pro to 2 million token context window.
GPT-4 Turbo 128K Context
OpenAI expands GPT-4 Turbo to 128K tokens with improved retrieval over long documents.
Claude 3 200K Context
Anthropic releases Claude 3 with 200K context window and improved long-context performance.
Gemini 1.5 Pro 1M Context Window
Google releases Gemini 1.5 Pro with 1 million token context window, 10x previous limits.