mlsanityData to 14 Oct 2026

Those Aren't Your Memories, They're Somebody Else's: Seeding Misinformation in Chat Bot Memories

arXiv 2304.05371 ↗First posted 6 Apr 2023cs.CL cs.AI cs.CRcited by 1

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Abstract (arXiv)

One of the new developments in chit-chat bots is a long-term memory mechanism that remembers information from past conversations for increasing engagement and consistency of responses. The bot is designed to extract knowledge of personal nature from their conversation partner, e.g., stating preference for a particular color. In this paper, we show that this memory mechanism can result in unintended behavior. In particular, we found that one can combine a personal statement with an informative statement that would lead the bot to remember the informative statement alongside personal knowledge in its long term memory. This means that the bot can be tricked into remembering misinformation which it would regurgitate as statements of fact when recalling information relevant to the topic of conversation. We demonstrate this vulnerability on the BlenderBot 2 framework implemented on the ParlAI platform and provide examples on the more recent and significantly larger BlenderBot 3 model. We generate 150 examples of misinformation, of which 114 (76%) were remembered by BlenderBot 2 when combined with a personal statement. We further assessed the risk of this misinformation being recalled after intervening innocuous conversation and in response to multiple questions relevant to the injected memory. Our evaluation was performed on both the memory-only and the combination of memory and internet search modes of BlenderBot 2. From the combinations of these variables, we generated 12,890 conversations and analyzed recalled misinformation in the responses. We found that when the chat bot is questioned on the misinformation topic, it was 328% more likely to respond with the misinformation as fact when the misinformation was in the long-term memory.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 26 references that are in the map. First posted on arXiv 6 Apr 2023.

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11 of 26 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 692
  4. 2020Recipes for building an open-domain chatbotcited by 593
  5. 2022A Holistic Approach to Undesired Content Detection in the Real Worldcited by 356
  6. 2021Beyond Goldfish Memory: Long-Term Open-Domain Conversationcited by 267
  7. 2021Internet-Augmented Dialogue Generationcited by 217
  8. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 198
  9. 2020Recipes for Safety in Open-domain Chatbotscited by 170
  10. 2017ParlAI: A Dialog Research Software Platformcited by 139
  11. 2021Hidden Backdoors in Human-Centric Language Modelscited by 90

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