COMPLETED
Research
MemoryCompiler
Memory compression framework for long conversations based on compiler optimization theory
// DESCRIPTION
MemoryCompiler treats dialogue memory compression as a compiler optimization problem, using techniques from program analysis to compress conversation history.
Core Concept
Just as compilers optimize code through multiple passes, MemoryCompiler optimizes memory through:
- Memory IR: Intermediate representation for entities, facts, and relations
- Dead Memory Elimination: Remove irrelevant historical information
- Fact Folding: Merge redundant facts
- Temporal Compression: Compress time-related information
- Importance Pruning: Keep only salient memories
Evaluation
Tested on MSC, LoCoMo, LongBench, and MultiWOZ datasets.
// HIGHLIGHTS
- Novel compiler-inspired approach to memory compression
- Multi-pass optimization pipeline
- Comprehensive evaluation suite
- v1.0 stable release