ImplicitMemBench: Measuring Unconscious Behavioral Adaptation in Large Language Models
Existing memory benchmarks for LLM agents evaluate explicit recall of facts, yet overlook implicit memory where experience becomes automated behavior without conscious retrieval. This gap is critical: effective assistants must automatically apply learned procedures or avoid failed actions without explicit reminders. We introduce ImplicitMemBench, the first systematic benchmark evaluating implicit memory through three cognitively grounded constructs drawn from standard cognitive-science accounts of non-declarative memory: Procedural Memory (one-shot skill acquisition after interference), Priming (theme-driven bias via paired experimental/control instances), and Classical Conditioning (Cond...
| Authors | Chonghan Qin, Xiachong Feng, Weitao Ma et al. |
|---|---|
| Primary category | cs.AI |
| Published | 9 April 2026 |
| Last updated at source | 15 April 2026 |
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