🚨Excited to announce our workshop Context Beyond the Window hosted at COLM in SF! 🚨
LLMs have finite context windows, yet real-world tasks demand absorbing, retaining, and acting on information that far exceeds any single prompt.
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We're looking for submissions across:
https://context-beyond-window.github.io/
• Context compression 🧃 — token compaction, recursive subagent calls, and external memory for storing and retrieving information
• Efficient architectures 🚀 — sub-quadratic attention variants that make extremely long context computationally feasible
• Continual training 🌱 — test-time training on streaming data, context distillation, and knowledge accumulation through continued pre-training
• Agentic memory systems 🐘 — scaffolds and test-time scaling techniques that improve knowledge retention and acquisition in LLMs
• Evaluation 🎯 — benchmarking models on increasingly long-horizon tasks