Towards a Middleware for Large Language Models | Paper Citation Record

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This paper cites Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng.

Towards a Middleware for Large Language Models Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng

Reference 1

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Observation 14d2ff2c-6554-4c25-becb-213c911196d3 · outbound

This paper cites Gpt-4 technical report, 2024.

Towards a Middleware for Large Language Models Gpt-4 technical report, 2024

Reference 2

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Observation 98f5732b-5b7d-4267-baa5-d690e2546ae8 · outbound

This paper cites Gqa: Training generalized multi-query transformer models from multi-head checkpoints, 2023.

Towards a Middleware for Large Language Models Gqa: Training generalized multi-query transformer models from multi-head checkpoints, 2023

Reference 3

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This paper cites Define the dialog to collect and confirm required informa- tion.

Towards a Middleware for Large Language Models Define the dialog to collect and confirm required informa- tion

Reference 4

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Observation 349cb893-87e9-4d77-ab51-46de2e0a9e33 · outbound

This paper cites Dialog management with alexa conversations.

Towards a Middleware for Large Language Models Dialog management with alexa conversations

Reference 5

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This paper cites Agents for amazon bedrock.

Towards a Middleware for Large Language Models Agents for amazon bedrock

Reference 6

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Observation c653ae20-2d71-456c-9659-e94cd0675e45 · outbound

This paper cites Meet claude.

Towards a Middleware for Large Language Models Meet claude

Reference 7

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Observation 86e55ba4-8391-4863-bd16-e5fcf4d77f01 · outbound

This paper cites GPTCache: An open-source semantic cache for LLM applications enabling faster answers and cost savings.

Towards a Middleware for Large Language Models GPTCache: An open-source semantic cache for LLM applications enabling faster answers and cost savings

Reference 8

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Observation 76644e5a-a4db-4d9b-b6bc-ca0d13a02c41 · outbound

This paper cites Pre-training Tasks for Embedding-based Large-scale Retrieval.

Towards a Middleware for Large Language Models Pre-training Tasks for Embedding-based Large-scale Retrieval

Reference 9

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Observation d4664fdb-a8e4-4b7a-bbaa-f238fed2cc7a · outbound

This paper cites Punica: Multi-tenant lora serving, 2023.

Towards a Middleware for Large Language Models Punica: Multi-tenant lora serving, 2023

Reference 10

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Observation e4798c56-045d-40c4-8af7-3ab9d84368e9 · outbound

This paper cites Frugalgpt: How to use large language models while reducing cost and improving performance, 2023.

Towards a Middleware for Large Language Models Frugalgpt: How to use large language models while reducing cost and improving performance, 2023

Reference 11

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Observation 8e33db0e-04b4-46ee-b511-f4e5d884e59e · outbound

This paper cites an unresolved cited work.

Towards a Middleware for Large Language Models Unresolved cited work

Reference 12

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Observation e58523d3-7a7c-4752-921c-9dce4680f354 · outbound

This paper cites an unresolved cited work.

Towards a Middleware for Large Language Models Unresolved cited work

Reference 13

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Observation fc3b923d-4e1f-4c07-9e82-0f17da0bef12 · outbound

This paper cites Llm inference performance engineering: Best practices.

Towards a Middleware for Large Language Models Llm inference performance engineering: Best practices

Reference 14

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Observation 9cd42ad0-ad0d-40b9-b61c-9fb8eac2ef59 · outbound

This paper cites Challenges in service discovery for microservices deployed in a kubernetes cluster–a case study.

Towards a Middleware for Large Language Models Challenges in service discovery for microservices deployed in a kubernetes cluster–a case study

Reference 15

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Observation 73ed9092-a236-4815-95c9-46df8d2fc137 · outbound

This paper cites Direct access, High-Performance memory disaggregation with DirectCXL.

Towards a Middleware for Large Language Models Direct access, High-Performance memory disaggregation with DirectCXL

Reference 16

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Observation 3bb140e2-4a55-494d-aed1-f763901c6c21 · outbound

This paper cites Service location protocol: Automatic discovery of ip network services.

Towards a Middleware for Large Language Models Service location protocol: Automatic discovery of ip network services

Reference 17

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Observation f8aeecc9-31de-44b7-bd75-4cb4dedb9841 · outbound

This paper cites Learning multiple layers of representation.Trends in cognitive sciences, 11(10):428–434, 2007.

Towards a Middleware for Large Language Models Learning multiple layers of representation.Trends in cognitive sciences, 11(10):428–434, 2007

Reference 18

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Observation 0ff26741-83f7-4f5a-a40d-f65a15cf48c8 · outbound

This paper cites Llm-adapters: An adapter family for parameter-efficient fine-tuning of large language models.

Towards a Middleware for Large Language Models Llm-adapters: An adapter family for parameter-efficient fine-tuning of large language models

Reference 19

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This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions, 2023.

Towards a Middleware for Large Language Models A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions, 2023

Reference 20

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Observation df9114f2-c1af-4f1a-bf72-a54d4e9359a8 · outbound

This paper cites Continuous delivery: reliable software releases through build, test, and deployment automation.

Towards a Middleware for Large Language Models Continuous delivery: reliable software releases through build, test, and deployment automation

Reference 21

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This paper cites do you follow me?.

Towards a Middleware for Large Language Models do you follow me?

Reference 22

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Observation f13a5e1d-f4aa-4f74-9b8a-bd4c2bd0ca27 · outbound

This paper cites Towards mitigating llm hallucination via self reflection.

Towards a Middleware for Large Language Models Towards mitigating llm hallucination via self reflection

Reference 23

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Observation b1f4b182-db1e-47ed-a17d-6b914ec5b32a · outbound

This paper cites Colbert: Efficient and effective passage search via contextualized late interaction over bert.

Towards a Middleware for Large Language Models Colbert: Efficient and effective passage search via contextualized late interaction over bert

Reference 24

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Observation 44e6ba19-8784-4328-b5da-57c050588348 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Towards a Middleware for Large Language Models Imagenet classification with deep convolutional neural networks

Reference 25

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This paper cites A survey on out-of-distribution detection in nlp, 2023.

Towards a Middleware for Large Language Models A survey on out-of-distribution detection in nlp, 2023

Reference 26

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This paper cites Conceptual guide.

Towards a Middleware for Large Language Models Conceptual guide

Reference 27

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Observation e29f21d6-440d-44d8-bc37-f4a8d6b97663 · outbound

This paper cites Langsmith tracing.

Towards a Middleware for Large Language Models Langsmith tracing

Reference 28

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This paper cites Machine learning in bioinformatics.

Towards a Middleware for Large Language Models Machine learning in bioinformatics

Reference 29

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Observation 420f658c-3acd-45f0-94c7-8d53e062bb66 · outbound

This paper cites Dialogue state tracking with a language model using schema-driven prompting.

Towards a Middleware for Large Language Models Dialogue state tracking with a language model using schema-driven prompting

Reference 30

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This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Towards a Middleware for Large Language Models Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 31

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Observation ee0c1802-a204-45b0-b5e3-7c3b67df61a1 · outbound

This paper cites Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.

Towards a Middleware for Large Language Models Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls

Reference 32

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This paper cites Proactive conversational agents in the post-chatgpt world.

Towards a Middleware for Large Language Models Proactive conversational agents in the post-chatgpt world

Reference 33

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This paper cites A high performance, scalable dns service for very large scale container cloud platforms.

Towards a Middleware for Large Language Models A high performance, scalable dns service for very large scale container cloud platforms

Reference 34

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Observation dbfe6260-cdf9-484b-b658-8dc58fd4aaf9 · outbound

This paper cites Gonzalez, Ion Stoica, and Matei Zaharia.

Towards a Middleware for Large Language Models Gonzalez, Ion Stoica, and Matei Zaharia

Reference 35

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This paper cites Learn- ing under concept drift: A review.

Towards a Middleware for Large Language Models Learn- ing under concept drift: A review

Reference 36

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This paper cites PrivateGPT.

Towards a Middleware for Large Language Models PrivateGPT

Reference 37

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Observation 291f415c-8d6d-49c0-b60c-657aa708ea85 · outbound

This paper cites In defense of dual-encoders for neural ranking.

Towards a Middleware for Large Language Models In defense of dual-encoders for neural ranking

Reference 38

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This paper cites A qualitative study of application-level caching.

Towards a Middleware for Large Language Models A qualitative study of application-level caching

Reference 39

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This paper cites Introducing meta llama 3: The most capable openly available llm to date.

Towards a Middleware for Large Language Models Introducing meta llama 3: The most capable openly available llm to date

Reference 40

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This paper cites Large language models: A survey, 2024.

Towards a Middleware for Large Language Models Large language models: A survey, 2024

Reference 41

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This paper cites Agile cold starts for scalable serverless.

Towards a Middleware for Large Language Models Agile cold starts for scalable serverless

Reference 42

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Observation 9d8bb22d-dc8f-4154-b836-5e8690b6f36b · outbound

This paper cites Effi- cient large-scale language model training on gpu clusters using megatron-lm.

Towards a Middleware for Large Language Models Effi- cient large-scale language model training on gpu clusters using megatron-lm

Reference 43

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This paper cites Applications of large language models (llms) in business analytics–exemplary use cases in data preparation tasks.

Towards a Middleware for Large Language Models Applications of large language models (llms) in business analytics–exemplary use cases in data preparation tasks

Reference 44

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This paper cites Aladdin: Joint placement and scaling for slo-aware llm serving, 2024.

Towards a Middleware for Large Language Models Aladdin: Joint placement and scaling for slo-aware llm serving, 2024

Reference 45

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This paper cites Overview of seldon core components ⁄pilcrow.

Towards a Middleware for Large Language Models Overview of seldon core components ⁄pilcrow

Reference 46

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This paper cites Semantics-based automated service discovery.

Towards a Middleware for Large Language Models Semantics-based automated service discovery

Reference 47

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This paper cites Efficiently scaling transformer inference.

Towards a Middleware for Large Language Models Efficiently scaling transformer inference

Reference 48

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This paper cites Pratheek, Neha Jawalkar, and Arkaprava Basu.

Towards a Middleware for Large Language Models Pratheek, Neha Jawalkar, and Arkaprava Basu

Reference 49

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This paper cites Overview of seldon core components ⁄pilcrow.

Towards a Middleware for Large Language Models Overview of seldon core components ⁄pilcrow

Reference 50

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This paper cites Continuous integration, delivery and deployment: a systematic review on approaches, tools, challenges and practices.

Towards a Middleware for Large Language Models Continuous integration, delivery and deployment: a systematic review on approaches, tools, challenges and practices

Reference 51

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Observation c86cf3d2-6cdc-4b65-9c6e-9eec9a42ff3f · outbound

This paper cites Fast transformer decoding: One write-head is all you need, 2019.

Towards a Middleware for Large Language Models Fast transformer decoding: One write-head is all you need, 2019

Reference 52

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This paper cites Megatron-lm: Training multi-billion parameter language models using model parallelism, 2020.

Towards a Middleware for Large Language Models Megatron-lm: Training multi-billion parameter language models using model parallelism, 2020

Reference 53

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Observation d1204c28-6172-4230-973f-16586be15725 · outbound

This paper cites Computer vision.

Towards a Middleware for Large Language Models Computer vision

Reference 54

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This paper cites Gptcache : A library for creating semantic cache for llm queries.

Towards a Middleware for Large Language Models Gptcache : A library for creating semantic cache for llm queries

Reference 55

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Towards a Middleware for Large Language Models Creating large language model applications utilizing langchain: A primer on developing llm apps fast

Reference 56

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Reference 57

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This paper cites Attention Is All You Need.

Towards a Middleware for Large Language Models Attention Is All You Need

Reference 58

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Towards a Middleware for Large Language Models Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 59

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Towards a Middleware for Large Language Models Raise a child in large language model: Towards effective and generalizable fine-tuning

Reference 60

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Observation 595d650d-5b6c-47ae-b7b7-c13d14f59bdd · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Towards a Middleware for Large Language Models Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 61

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Towards a Middleware for Large Language Models React: Synergizing reasoning and acting in language models, 2023

Reference 62

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This paper cites Deltazip: Multi-tenant language model serving via delta compression, 2023.

Towards a Middleware for Large Language Models Deltazip: Multi-tenant language model serving via delta compression, 2023

Reference 63

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Towards a Middleware for Large Language Models A survey on large language model (llm) security and privacy: The good, the bad, and the ugly

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T15:33:15.924909Z

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This paper cites Nomad-attention: Efficient llm inference on cpus through multiply- add-free attention, 2024.

Towards a Middleware for Large Language Models Nomad-attention: Efficient llm inference on cpus through multiply- add-free attention, 2024

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:33:16.208367Z

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Observation b0132bab-5119-464f-a8ad-53c870084b0f · outbound

This paper cites Explainability for large language models: A survey, 2023.

Towards a Middleware for Large Language Models Explainability for large language models: A survey, 2023

Reference 66

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This paper cites Service discovery in pervasive computing environments.

Towards a Middleware for Large Language Models Service discovery in pervasive computing environments

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:33:16.175779Z

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Observation 38e8ec52-9811-486a-9a0a-9c4bd2534630 · outbound

This paper cites Large language models for information retrieval: A survey.

Towards a Middleware for Large Language Models Large language models for information retrieval: A survey

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T15:33:15.959531Z

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This paper cites Large Language Models are Built-in Autoregressive Search Engines.

Towards a Middleware for Large Language Models Large Language Models are Built-in Autoregressive Search Engines

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T15:33:15.964358Z

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