Public articles linked to the same research event.
arXiv The authors identify and study memory overreliance, an inference-time failure in which benign, correctly stored, and appropriately retrieved memory misleads reasoning when it only partially overlaps the current query, and propose MemTrim, a plug-and-play framework that decomposes memories into evidence units indexed in a trie at write time and, at read time, removes evidence repeated in or conflicting with the query, retains memory-only information, and suppresses a previous answer when its supporting evidence has changed, reducing memory-induced errors across benchmarks, models, and memory architectures while preserving the benefits of useful memory.
The authors identify and study memory overreliance, an inference-time failure in which benign, correctly stored, and appropriately retrieved memory misleads reasoning when it only partially overlaps the current query, and propose MemTrim, a plug-and-play framework that decomposes memories into evidence units indexed in a trie at write time and, at read time, removes evidence repeated in or conflicting with the query, retains memory-only information, and suppresses a previous answer when its supporting evidence has changed, reducing memory-induced errors across benchmarks, models, and memory architectures while preserving the benefits of useful memory.
The authors identify and study memory overreliance, an inference-time failure in which benign, correctly stored, and appropriately retrieved memory misleads reasoning when it only partially overlaps the current query, and propose MemTrim, a plug-and-play framework that decomposes memories into evidence units indexed in a trie at write time and, at read time, removes evidence repeated in or conflicting with the query, retains memory-only information, and suppresses a previous answer when its supporting evidence has changed, reducing memory-induced errors across benchmarks, models, and memory architectures while preserving the benefits of useful memory.
The authors identify and study memory overreliance, an inference-time failure in which benign, correctly stored, and appropriately retrieved memory misleads reasoning when it only partially overlaps the current query, and propose MemTrim, a plug-and-play framework that decomposes memories into evidence units indexed in a trie at write time and, at read time, removes evidence repeated in or conflicting with the query, retains memory-only information, and suppresses a previous answer when its supporting evidence has changed, reducing memory-induced errors across benchmarks, models, and memory architectures while preserving the benefits of useful memory.