Papers with key-value memory
Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge (P18-1)
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| Challenge: | a new model for reading comprehension integrates external commonsense knowledge . cloze-style reading comprehension is a language understanding task similar to question answering . |
| Approach: | They propose a reading comprehension model that integrates external commonsense knowledge in a cloze-style setting. |
| Outcome: | The proposed model improves results over a very strong baseline on a hard Common Nouns dataset, making it a strong competitor of more complex models. |
Memory-Based Invariance Learning for Out-of-Domain Text Classification (2023.emnlp-main)
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| Challenge: | Existing approaches to learning invariant representations rely on the assumption that training and test sets come from the same domain. |
| Approach: | They propose to extend a classification model trained on multiple source domains to an unseen target domain by using key-value memory. |
| Outcome: | The proposed method improves on sentiment analysis and natural language inference tasks. |
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks (2022.emnlp-main)
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| Challenge: | Existing methods rely on parametric models that store knowledge in parameters or retrieval-augmented models that have access to external knowledge sources. |
| Approach: | They propose a parametric parametric model that stores knowledge in its parameters or a retrieval-augmented model that has access to external knowledge sources. |
| Outcome: | The proposed method runs substantially faster across the board and produces more accurate results on WoW and ELI5. |
Sample Efficient Alignment Learning With Episodic Control (2025.findings-emnlp)
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| Challenge: | Existing parametric methods for aligning large language models with task objectives are limited. |
| Approach: | They propose a non-parametric framework that aligns large language models with task objectives . they use a key-value memory to store associations between generated text and its corresponding values . |
| Outcome: | The proposed framework outperforms state-of-the-art baselines on harmless, helpful, and summarization tasks. |
Dynamic Steering With Episodic Memory For Large Language Models (2025.findings-acl)
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| Challenge: | Existing activation steering methods apply a single sentence-level steering vector uniformly across all tokens, ignoring LLMs’ token-wise, auto-regressive nature. |
| Approach: | They propose a framework that aligns LLMs to given demonstrations by steering at the token level conditioned on the input query. |
| Outcome: | The proposed framework surpasses baselines across safety, style transfer, and role-playing tasks, demonstrating improved alignment as demonstration scales. |