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
Make Your LVLM KV Cache More Lightweight
Anonymous (ICLR and TMLR drafts; arXiv metadata lists named authors)
ObjectGraph: From Document Injection to Knowledge Traversal — A Native File Format for the Agentic Era
Mohit Dubey, Open Gigantic
Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling
Keming Wu, Zuhao Yang, Kaichen Zhang +19 more
Synthetic Computers at Scale for Long-Horizon Productivity Simulation
Tao Ge, Baolin Peng, Hao Cheng +1 more
LogicPoison: Logical Attacks on Graph Retrieval-Augmented Generation
Yilin Xiao, Jin Chen, Qinggang Zhang +6 more
Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning
Yuhang Wu, Xiangqing Shen, Fanfan Wang +4 more
Neuro-RIT: Neuron-Guided Instruction Tuning for Robust Retrieval-Augmented Language Model
Jaemin Kim, Jae O Lee, Sumyeong Ahn +1 more
Diffusion Language Models Are Natively Length-Aware
Vittorio Rossi, Giacomo Cirò, Davide Beltrame +3 more
LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation
Koki Itai, Shunichi Hasegawa, Yuta Yamamoto +2 more
FlashPrefill: Instantaneous Pattern Discovery and Thresholding for Ultra-Fast Long-Context Prefilling
Qihang Fan, Huaibo Huang, Zhiying Wu +3 more
Recent Milestones
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.