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Towards Optimal Caching and Model Selection for Large Model Inference
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Batching, caching and other optimization techniques are routinely used as a means to improve the scaling of AI, allowing more users to interact with ever more powerful technologies.
“In fact, batching, caching and other optimization techniques are routinely used as a means to improve the scaling of AI, allowing more users to interact with ever more powerful technologies [93, 141].”
From From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debate (2025) · cites this paper as [141]
Citations
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Cited by 2
Metadata
- Authors
- Zhu, B., Sheng, Y., Zheng, L., Barrett, C., Jordan, M., & Jiao, J.
- Venue
- Advances in Neural Information Processing Systems 36
- Published
- 2023
- Pages
- 59062-59094
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133199121
- Cited by
- 2
- References
- 0
- Citations by year
- 2026: 2
- FWCI
- 0.36
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Networks and Communications › Caching and Content Delivery
- Keywords
- large language model inference, caching, model selection, inference optimization, prompt caching
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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