Make Memory work for you.

Give Your Coding Agents a Memory You Own

MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use

arXiv:2608. 20202v1 Announce Type: new Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions.

MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use

Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing memory benchmarks mainly evaluate whether information is correctly extracted, stored, and retrieved, while largely overlooking how retrieved memories reshape model reasoning and affect performance on the current task.

Context Windows Forget What Matters — I Built a Usage-Reinforced Decay Engine for AI Agent Memory

Most AI memory systems keep the newest information—not the most important. Here's how I used the Ebbinghaus forgetting curve to build a better memory engine for LLMs.

Dreaming: Better memory for a more helpful ChatGPT

ChatGPT introduces a new memory system to better remember preferences, keeping context fresh and relevant across conversations.

AutoMem: Automated Learning of Memory as a Cognitive Skill

arXiv:2607. 01224v1 Announce Type: new Abstract: Memory expertise is a learned skill: knowing what to encode, when to retrieve, and how to organize knowledge--a capacity known in cognitive science as metamemory.