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Paper Citation Record · LEDGER

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications

As of 14 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2412.18695.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.18695 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:38:25.630673Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy39
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99928eec-c128-4ca8-a7f7-e2a13fd6493a · outbound

This paper cites https://github.c om/vllm-project/vllm, 2024.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications https://github.c om/vllm-project/vllm, 2024

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:27.848114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.243032Z digest=sha256:7ab952ffc2ed594aa1ee91672ecea8f153af2bec0c0f552d5690fc3c2f7c305e

Observation 395a7211-d1e2-4263-8129-2699c69bebc3 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.272878Z digest=sha256:5b07585ca1d8d9c499c0acca50781e36e38f6123e9d550cf8d452e1294cf2af8

Observation 0aee1008-3364-4a96-970e-dc3bd3eb5095 · outbound

This paper cites Infercept: Efficient intercept support for augmented large language model inference.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Infercept: Efficient intercept support for augmented large language model inference

Reference 3

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raw_fallback, observed 2026-08-11T04:38:27.836564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.327030Z digest=sha256:ae427e8e74524c42db78bd2c0f60be6b2c6b80cd50a7cdfa98a3f713d34659d8

Observation dd836487-3e62-4897-addf-2675eafba803 · outbound

This paper cites GPT-4 Technical Report.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications GPT-4 Technical Report

Reference 4

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:38:24.386208Z digest=sha256:eb6d91d84785daa37115e483d4695a9099f162aaa0489614159c7696a1b3aabb

Observation 0b195bd6-3279-4460-9867-4f323721e703 · outbound

This paper cites Taming throughput-latency tradeoff in llm inference with sarathi-serve.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Taming throughput-latency tradeoff in llm inference with sarathi-serve

Reference 5

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raw_fallback, observed 2026-08-11T04:38:27.770990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.447658Z digest=sha256:44c9e3b0c37a69ea19f29487c16e75e3526c571e870ae896f24c5594bd8a73f3

Observation aaf54535-a78c-4272-8ee4-e5826e64771a · outbound

This paper cites Utility accrual real-time scheduling under variable cost functions.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Utility accrual real-time scheduling under variable cost functions

Reference 6

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raw_fallback, observed 2026-08-11T04:38:27.628700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.484523Z digest=sha256:58b4f42faf2f19ad371508372ac6e1bf48a9e36ab6272012d5cb8ec3108ca96b

Observation 68f8db8f-3032-4d1c-94b5-b78888e8a17f · outbound

This paper cites An evaluation model for information distribution in multi-robot systems.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications An evaluation model for information distribution in multi-robot systems

Reference 7

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raw_fallback, observed 2026-08-11T04:38:27.602025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.565139Z digest=sha256:758110117d988ec591dca6d7a0219cd2a0ddc0da4911bb156c1b650d3ef94ab1

Observation 0c40ae0f-dee3-443b-a33c-99f958cbf217 · outbound

This paper cites Language Models are Few-Shot Learners.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Language Models are Few-Shot Learners

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:38:24.574581Z digest=sha256:32c085de64eb91c3b62c6c29bf10341ff6b5795dfa3726b405576946f10a6b5f

Observation 6960a155-4972-4932-84b3-85a834670797 · outbound

This paper cites Drone detection using depth maps.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Drone detection using depth maps

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.587951Z digest=sha256:75876215cf74a1e3fa0ffe7a8d38c99e525e894eff3316bc6942a67e9a9a8799

Observation 25888fd1-9ea5-4c5a-888d-b9a38d38729a · outbound

This paper cites TypeFly: Flying Drones with Large Language Model.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications TypeFly: Flying Drones with Large Language Model

Reference 10

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source=pdf_text observed=2026-08-11T04:38:24.608098Z digest=sha256:d26fb597a66bfc99ffa58b6c56aa5d583be66bc90a421728043918a98d3b89d4

Observation ecbe4b49-29e5-485f-a789-d190aa04502a · outbound

This paper cites A scheduling algorithm for tasks described by time value function.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications A scheduling algorithm for tasks described by time value function

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.612490Z digest=sha256:4d941d190a057626366c2f4964b65a0d3c06601c71a5656b5891ab831ac15403

Observation b78ca992-48c8-4396-8f3a-d6d9c39cc375 · outbound

This paper cites Robots that can chat.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Robots that can chat

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.616334Z digest=sha256:6aab105eb28a38bf1f610be8262538ad07e4dccfcd4a5a4c552bf9070149ac74

Observation 585e45ac-466f-4b8a-a364-60eb64186d6d · outbound

This paper cites Number of parameters in gpt-4.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Number of parameters in gpt-4

Reference 13

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raw_fallback, observed 2026-08-11T04:38:27.487427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.620187Z digest=sha256:a47da7595086c66fc8afb3a43864191809e0d7f87381ad48360bb7079b2c442a

Observation e34ba0eb-10ed-4f8e-899d-8a047456c567 · outbound

This paper cites Transformers: State-of-the-art machine learning for pytorch, tensorflow, and jax.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Transformers: State-of-the-art machine learning for pytorch, tensorflow, and jax

Reference 14

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raw_fallback, observed 2026-08-11T04:38:27.311267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.623493Z digest=sha256:622a723bd0bd0bde1681f1403d4b2ea5480b20d86e9f13719d6a1b0d8bedb257

Observation d8f2c8b7-6ac5-4b75-8ed5-fe8dedcd5281 · outbound

This paper cites Hierarchical Neural Story Generation.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Hierarchical Neural Story Generation

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.627595Z digest=sha256:b01b9eb769ae14c88ff565379b0e6692f86a0788af214f107a5637f43caca26a

Observation 55b13b88-5217-4d8a-abda-8393eeed75fa · outbound

This paper cites Figure + openai allow speech-to-speech reasoning over learned behaviors.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Figure + openai allow speech-to-speech reasoning over learned behaviors

Reference 16

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raw_fallback, observed 2026-08-11T04:38:27.216278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.637982Z digest=sha256:15c11a1fbbfbd009f3cf43883846471058dec0e977f5be02ec6dde7bc927b468

Observation f3b5f765-da64-478d-b8b9-c2bb9a5cea34 · outbound

This paper cites Efficient LLM Scheduling by Learning to Rank.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Efficient LLM Scheduling by Learning to Rank

Reference 17

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source=pdf_text observed=2026-08-11T04:38:24.653256Z digest=sha256:c882e2058d7a4075405272bc86cda674520e63f411be76e1c2ea2c0a23e11396

Observation 298ddeae-864a-4d2d-8a4d-261e569a04c3 · outbound

This paper cites Prompt cache: Modular attention reuse for low-latency inference.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Prompt cache: Modular attention reuse for low-latency inference

Reference 18

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.676877Z digest=sha256:eaaa3834d1534e161c09179acb26d2ac2203388fe92ddfdd7d240a51c5f7b27d

Observation fac64749-c89e-4a29-bd29-5fc9c2ab5f2b · outbound

This paper cites GPT-4o System Card.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications GPT-4o System Card

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.724781Z digest=sha256:7c378101b38fc35b90abe6a619ed8136cfde76530cc0813108b635b1b8544633

Observation e9cff7bf-3c15-45fa-ae34-2beb8418754e · outbound

This paper cites A time- driven scheduling model for real-time operating systems.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications A time- driven scheduling model for real-time operating systems

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-11T04:38:27.193263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.766307Z digest=sha256:95a991626f8da9ff36a0d57a7428c3ccba918cdc2768e581823ef51d5f5cba3c

Observation 2f3eee56-fbb5-466e-8458-7189026e0a0e · outbound

This paper cites Coedge: A co- operative edge system for distributed real-time deep learning tasks.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Coedge: A co- operative edge system for distributed real-time deep learning tasks

Reference 21

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raw_fallback, observed 2026-08-11T04:38:27.177228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.820179Z digest=sha256:17dcfd28945177a1bd68a76ff1691cf2ce92647c045b72e8aafe9a75e94d8404

Observation 43e01fc5-d675-465e-8e1a-1aee8c27e62e · outbound

This paper cites 𝑠3: Increasing gpu utilization during generative inference for higher throughput.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications 𝑠3: Increasing gpu utilization during generative inference for higher throughput

Reference 22

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.870994Z digest=sha256:d089cf56a19b995b952513a7d9048a88cf4bd3f04a0bdacddd53266b3c07d83b

Observation 081ecc48-058f-4754-bec5-312bd046c9dc · outbound

This paper cites An LLM Compiler for Parallel Function Calling.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications An LLM Compiler for Parallel Function Calling

Reference 23

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source=pdf_text observed=2026-08-11T04:38:24.901003Z digest=sha256:1be735979cd61738063e74de83cfd5bbf4dff584867589fbc62d00aebc12add3

Observation a61c66f3-5dc1-4a5b-80ed-df7299dd09ad · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Gonzalez, Hao Zhang, and Ion Stoica

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.920252Z digest=sha256:856c8e0a1ada428702ede3f88a95d90dce3c559f422162fd2c4cecc00cefc677

Observation f7ca6d68-ac17-4a0a-99a8-8a71c6413a0d · outbound

This paper cites Mobilegpt: Augment- ing llm with human-like app memory for mobile task automation.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Mobilegpt: Augment- ing llm with human-like app memory for mobile task automation

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.931709Z digest=sha256:5540c1f9860a1c88fa405e67cb7dcd06554ba9c78f98ebc7b51a44135f2bdc54

Observation d80e1ed3-e31d-4cde-b746-0f0259d84b23 · outbound

This paper cites A utility accrual scheduling algorithm for real-time activities with mu- tual exclusion resource constraints.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications A utility accrual scheduling algorithm for real-time activities with mu- tual exclusion resource constraints

Reference 26

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raw_fallback, observed 2026-08-11T04:38:26.964842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.940518Z digest=sha256:acd16745ab8a80528eb571bdfcd992cba3ed09c19d3000071f297e73676fe9c8

Observation efdb42c8-0623-4f44-a707-e0771553472d · outbound

This paper cites REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.944589Z digest=sha256:6f86a4e74f717d73800f15ac7055a80b674a8c748395d44348dc6ff9971462ed

Observation bba860fa-66d2-45b7-9009-ebedc2b0f11c · outbound

This paper cites An example real-time command, control, and battle management application for alpha.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications An example real-time command, control, and battle management application for alpha

Reference 28

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raw_fallback, observed 2026-08-11T04:38:26.836295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.948919Z digest=sha256:9b446fbce01542c5879e354dc3e663c2f53482ffe7c080c7a21f20ba31db9dab

Observation ef50c6b3-049a-4522-83ac-d1f8bc0b38ed · outbound

This paper cites The llama 3 herd of models.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications The llama 3 herd of models

Reference 29

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raw_fallback, observed 2026-08-11T04:38:26.801059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.957460Z digest=sha256:0f482648e04bae882dec539c49e832535933a884253f6531b6fa03d66237d011

Observation 02d90645-8b53-4d0f-b5a8-bf00bbccae1f · outbound

This paper cites Meta ai assistant built with llama 3.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Meta ai assistant built with llama 3

Reference 30

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raw_fallback, observed 2026-08-11T04:38:26.775272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.968585Z digest=sha256:e64a3b77c6799863368bfac3dcea80d87ef9616103d56229cd0ca21b6e3577b8

Observation f5418bd6-6ed8-4275-b3f2-0de38cf0fa48 · outbound

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

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Introducing meta llama 3: The most capable openly available llm to date

Reference 31

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raw_fallback, observed 2026-08-11T04:38:26.753419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.975538Z digest=sha256:ef1005fabc91581060d2c7df0e33f26bfa41827350fdf33ad90ff9d4c81e19f3

Observation 3ccbaa84-3693-448d-8894-741444196932 · outbound

This paper cites Llama 2 70B: An MLPerf Inference Benchmark for Large Language Models.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Llama 2 70B: An MLPerf Inference Benchmark for Large Language Models

Reference 32

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raw_fallback, observed 2026-08-11T04:38:26.710242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.979568Z digest=sha256:c3a5e258a68bdf5cdf82c0dfdbb0dce167afa8fda5fee8f4c816d6c18aeaa77d

Observation 074bf257-205d-43c6-bdd3-558442656e2b · outbound

This paper cites Neuromeka indy.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Neuromeka indy

Reference 33

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raw_fallback, observed 2026-08-11T04:38:26.701408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.983843Z digest=sha256:413235833566f863bed35e78960df5c1824499b24283aa609c6574d08fecb1eb

Observation 618f1dc9-a2a8-404f-8278-1b85c5e60eda · outbound

This paper cites Tensorrt-llm.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Tensorrt-llm

Reference 34

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raw_fallback, observed 2026-08-11T04:38:26.691756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.987907Z digest=sha256:208d6b798efd387d8779f16f57bbcdcf3a362ccea6e538c4c57b6a8ebba3b8b5

Observation 1a4ba292-3887-4393-a8be-041c9c5012eb · outbound

This paper cites Exegpt: Constraint-aware resource scheduling for llm inference.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Exegpt: Constraint-aware resource scheduling for llm inference

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.680139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:24.992302Z digest=sha256:c67371fb6fa65ea39e5998d6c5ad390fee71743e23502d3936da41f4af0f5d3d

Observation f07e6141-ba24-4158-ac85-9556aacde1cb · outbound

This paper cites Queue management for slo-oriented large language model serving.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Queue management for slo-oriented large language model serving

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:24.996442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:24.996442Z digest=sha256:67595296f251b8bc64174a2a510866f1cfcdfe23c39a4bf65f8d3639a4e5b60e

Observation 666d98ee-ddb4-4c64-b8cf-15ec1c8ccdc6 · outbound

This paper cites Managing delays in human- robot interaction.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Managing delays in human- robot interaction

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.656472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.000726Z digest=sha256:8c5ddb88d58937648522fc0380a1cd47048f2d3992d50116758b3152dfebe03b

Observation 7071a7fe-a514-4ba6-814e-9397c9703e09 · outbound

This paper cites Efficiently scaling transformer inference.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Efficiently scaling transformer inference

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.606296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.005056Z digest=sha256:1df2f224f68625e144666d47fdb3230e9c357896dc3ba2ce8a32e7700a01b870

Observation d407896f-c54b-482a-ba84-0ef671fcfe52 · outbound

This paper cites Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.029210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.029210Z digest=sha256:dc18de5a4e5939e566ee0c41020bf0b64fc061e6143f5a6229f75824012e15ab

Observation ab2a5bf0-36ef-4fa8-a527-f71db3dd0f19 · outbound

This paper cites SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.074571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.074571Z digest=sha256:deb44393b5ca7d53c47bde72f165514432caa51dbfdea4a0e5a3f8ec0a1826bd

Observation 6f594cc3-1de5-4e98-b9f7-c7bd10736450 · outbound

This paper cites Ravindran, E.D.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Ravindran, E.D

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.518176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.127352Z digest=sha256:e33bd4425c8b42d06600f7a5c9a24c4325e7a386b8f9982ef02619c73e7a97d6

Observation 03af85fc-1136-4001-bbfa-d85a3be6fcca · outbound

This paper cites Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.173656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.173656Z digest=sha256:75716a6991f5b40f8a5275c1c1e09d8f007827a799ca2ada0dd9b1a8e14712f6

Observation adcd4f3d-3dd5-4fce-932b-d824da396f10 · outbound

This paper cites Average reading speed.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Average reading speed

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.375375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.226187Z digest=sha256:3fadb207edc4b09008f19a14d5a81409df47505db69d135b8c162bdc47411dc1

Observation 189564b4-3e4e-4b9d-a134-53cb414100ee · outbound

This paper cites Revenue-driven scheduling in drone delivery networks with time-sensitive service level agreements.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Revenue-driven scheduling in drone delivery networks with time-sensitive service level agreements

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.340384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.246677Z digest=sha256:cc2d3c2b6ce719b4603caf240ecbbcb01ab0d016997d8a506d0048d9fcee1ef2

Observation 68210787-0793-4d55-ab2e-a2d45652f3d9 · outbound

This paper cites Don't Stop Me Now: Embedding Based Scheduling for LLMs.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Don't Stop Me Now: Embedding Based Scheduling for LLMs

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.260335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.260335Z digest=sha256:431b551ffa543f4194071fe10ced779a0a5e6c095e9cf40e8af46ff584dc46a5

Observation 73add5c7-41bf-41dc-8441-e310f172f34b · outbound

This paper cites Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.270207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.270207Z digest=sha256:492098a9ce8f9198bebdcf3db6a6ab057d05a967e582662494a0f99ba41633ca

Observation b7e64dd8-5970-4aa4-bd03-ae62b73acada · outbound

This paper cites Response time and display rate in human perfor- mance with computers.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Response time and display rate in human perfor- mance with computers

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.323463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.279474Z digest=sha256:236a2357df3d1484894eec8cb4ff813abd49b089d7152572497c77dc6927e2c7

Observation 8acdd9c5-ed87-4dd8-9d3b-06e3de664305 · outbound

This paper cites Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.285326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.285326Z digest=sha256:a39644655ab2a537f00b74dc5f9f08377cd9a64cec50e3cb5d478c1da0c5aaf3

Observation 5fe17180-805a-4a5c-82c6-a64ab40bbcbd · outbound

This paper cites Tello sdk user guide, 2023.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Tello sdk user guide, 2023

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.305980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.296865Z digest=sha256:e67b3f124e2b242654d883344c6d85bbde7a27ca1bd3a16d57c75aa3e58addb8

Observation 60cf42c0-46e3-4f84-a1da-c7457c6f731f · outbound

This paper cites Tidwell, R.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Tidwell, R

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.285433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.309491Z digest=sha256:88f22eebd2fb0ad08042357658fd7d99473b236f52dfbf1d4cae180b43b4e7aa

Observation 641bd73b-b0b4-4ce9-94f5-eb741e2e057b · outbound

This paper cites Optimizing expected time utility in cyber-physical systems schedulers.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Optimizing expected time utility in cyber-physical systems schedulers

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.254036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.324476Z digest=sha256:07f9f3a3da85bf105a88ffab8bdcdf6479e19e1c7a2a7f52f416391101014969

Observation bd6a5605-a431-4b60-969e-5fc87d3bc5bd · outbound

This paper cites Chatgpt for robotics: Design principles and model abilities.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Chatgpt for robotics: Design principles and model abilities

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.333152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.333152Z digest=sha256:5c8d290fb9896a29c5373cda005ea6ffbd09d5c587ff8414377aa370e1238e75

Observation cfd1c4c5-107c-49e1-86eb-b704ad565627 · outbound

This paper cites LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.337040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.337040Z digest=sha256:4e44a818a4fcec7064002f215909121304f0cc9c5abb4b6061de6c6886c09067

Observation c62736ec-0002-4176-aa75-9fb2af639824 · outbound

This paper cites Autodroid: Llm-powered task automation in android.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Autodroid: Llm-powered task automation in android

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.209410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.357810Z digest=sha256:7c25ed96bf38dbcf7d5077191408cc6116b389a4ddfb3e2791a2b87d88071bf5

Observation 60f7203e-25b4-4c43-aed9-380f931f13e6 · outbound

This paper cites Time-utility function — Wikipedia, 2024.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Time-utility function — Wikipedia, 2024

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.174380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.396599Z digest=sha256:1160dabdc32538655ea5696d397c1226cfeeaeba11d99a53a61ee4e6ead49869

Observation 39ed668f-4302-4242-9041-26e49bacdcbf · outbound

This paper cites Fast Distributed Inference Serving for Large Language Models.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Fast Distributed Inference Serving for Large Language Models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.427260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.427260Z digest=sha256:26b175232f029c87d65b486f279c29a31ae9d3bedc40eea3173bceb965cae9f7

Observation 40058a5d-c392-4189-88e8-91c0bc70e301 · outbound

This paper cites Utility accrual scheduling under arbitrary time/utility functions and multi-unit resource constraints.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Utility accrual scheduling under arbitrary time/utility functions and multi-unit resource constraints

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:26.111952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.453147Z digest=sha256:fb143d4e313ac3fe3ca58bac2510468fa9fa608d74af8ec2754c82428998f49e

Observation cb0dde80-536e-49f3-bd9d-6f46ab2a5349 · outbound

This paper cites Orca: A distributed serving system for {Transformer-Based} generative models.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Orca: A distributed serving system for {Transformer-Based} generative models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.499266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.499266Z digest=sha256:1265aa97fa386a488b1c2bf7cbb68592cce698887d65ccd6cadcb8b2a8b6917f

Observation 8dd46fec-4422-40e8-a7a5-12061308528c · outbound

This paper cites {SHEPHERD}: Serving{DNNs} in the wild.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications {SHEPHERD}: Serving{DNNs} in the wild

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:25.994566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.534928Z digest=sha256:155de58acabba120136a5e2d0b0e7d9b0b8e5f1970f9a56bef5545a6f7dfd23b

Observation 8b4a0efb-aace-4fd7-bd4b-de69f139f743 · outbound

This paper cites Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-11T04:38:25.558727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:38:25.558727Z digest=sha256:ef3d7076469068e1b83774595439b4c0a468f664a2d64dd7cae9f1786e2fc259

Observation 63756280-cb92-4452-b8d8-8f7b72a0b5fc · outbound

This paper cites Response length perception and sequence scheduling: An llm-empowered llm inference pipeline.Advances in Neural Information Processing Systems, 36, 2024.

TimelyLLM: Segmented LLM Serving System for Time-sensitive Robotic Applications Response length perception and sequence scheduling: An llm-empowered llm inference pipeline.Advances in Neural Information Processing Systems, 36, 2024

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:38:25.932349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T04:38:25.630673Z digest=sha256:2509aa700fef796ffe3240d83fe3b4b07a2375a18fd4fc757eddf0478195170b

Pith citing papers

No inbound Pith citation observations are available.