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Parallel Context Windows for Large Language Models
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Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.
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Context window adaptation techniques seek to extend the usable input length of LLMs by modifying attention mechanisms, positional encoding schemes, or input structures.
“Context window adaptation techniques seek to extend the usable input length of LLMs by modifying attention mechanisms, positional encoding schemes, or input structures.”
From From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms (2026) · cites this paper as Ratner et al., 2022
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“…to handle longer input contexts, including designing efficient training and finetuning schemes (Dao et al., 2022; Li et al., 2023b,a; Shi et al., 2023b) and inference-time methods that extend an LLM’s context length (Press et al., 2021; Ratner et al., 2023; Xiao et al., 2023; Bertsch et al., 2023).”
Metadata
- Authors
- Ratner, N., Levine, Y., Belinkov, Y., Ram, O., Magar, I., Abend, O., Karpas, E., Shashua, A., Leyton-Brown, K., & Shoham, Y.
- Corresponding author
- Ratner, Nir
- Venue
- Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2023
- Pages
- 6383-6402
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W4385570090
- Cited by
- 111
- References
- 10
- Citations by year
- 2026: 17 · 2025: 39 · 2024: 42 · 2023: 13
- FWCI
- 12.86
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by-sa)
- arXiv (Cornell University) (cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- large language models, context window size, long-range dependencies
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