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Paper Citation Record · LEDGER

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.00491.

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

pith.paper-citation-record.v1
2507.00491 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:20:29.524083Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

43 of 43 outbound references displayed

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  • unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f30dd63-5955-495a-965e-2f1156e104ca · outbound

This paper cites The shift from models to compound ai systems,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms The shift from models to compound ai systems,

Reference 1

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Observation 0f92b4a9-59cb-4958-a94a-14f6f77893ba · outbound

This paper cites Are more llm calls all you need? towards the scaling properties of compound ai systems,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Are more llm calls all you need? towards the scaling properties of compound ai systems,

Reference 2

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 52fc0a9f-9394-46a3-82de-250c5d6b8d99 · outbound

This paper cites Optimizing Model Selection for Compound AI Systems.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Optimizing Model Selection for Compound AI Systems

Reference 3

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Observation 1839f655-5ea1-40b2-87e4-919933da9d28 · outbound

This paper cites Can Large Language Models Really Improve by Self-critiquing Their Own Plans?.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Can Large Language Models Really Improve by Self-critiquing Their Own Plans?

Reference 4

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Observation 4d863ddb-f76b-48be-bbb9-9cb697fb2319 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 5

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Observation 21ebe740-188c-470e-864f-f2916425cdfc · outbound

This paper cites Drive as you speak: Enabling human-like interaction with large language models in au- tonomous vehicles,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Drive as you speak: Enabling human-like interaction with large language models in au- tonomous vehicles,

Reference 6

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Observation 73736cd7-c85f-48a2-ac6d-bfd1d9fb098a · outbound

This paper cites Langchain,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Langchain,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0eb6869b-84b5-45e0-90cb-07b82710963d · outbound

This paper cites Langbase: AI-Powered Multilingual Database,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Langbase: AI-Powered Multilingual Database,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0f141c2a-2ebf-4b8d-895a-bc2124e50dd1 · outbound

This paper cites Autoscale: Energy efficiency optimization for stochas- tic edge inference using reinforcement learning,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Autoscale: Energy efficiency optimization for stochas- tic edge inference using reinforcement learning,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fd622bec-2e00-4e47-884e-d804477bf876 · outbound

This paper cites Band: coordinated multi-dnn inference on heterogeneous mobile processors,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Band: coordinated multi-dnn inference on heterogeneous mobile processors,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b1aa7d77-5e9b-4d08-8f70-4de96011032d · outbound

This paper cites Automated exploration and implementation of distributed cnn inference at the edge,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Automated exploration and implementation of distributed cnn inference at the edge,

Reference 11

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 21a99e5d-657b-4cf9-ace6-85df081cbe92 · outbound

This paper cites Apple intelligence,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Apple intelligence,

Reference 12

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 1040303f-9781-472b-8f07-7bced09b5ae7 · outbound

This paper cites Meta ray-ban smart glasses: Next generation smart eyewear,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Meta ray-ban smart glasses: Next generation smart eyewear,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7dc3e2b3-801d-4bfc-b25d-e8c9aebace25 · outbound

This paper cites Apple vision pro: Spatial computing device,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Apple vision pro: Spatial computing device,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9ea5ba1d-0161-463b-9c0f-b53bf13db1e6 · outbound

This paper cites Qualcomm launches its next-generation xr and ar platforms,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Qualcomm launches its next-generation xr and ar platforms,

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e704bec9-1fc2-44b4-8209-d92b8f25ea28 · outbound

This paper cites Tango: Low latency multi-dnn inference on heterogeneous edge platforms,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Tango: Low latency multi-dnn inference on heterogeneous edge platforms,

Reference 16

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d1f88d78-fb39-4b60-b79a-d795a87e631b · outbound

This paper cites OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload,

Reference 17

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0b2db31c-0c0c-4b46-ae2e-c471e5e6360a · outbound

This paper cites MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference,

Reference 18

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Observation db9a214f-969c-42b1-92dd-2a6f406452a8 · outbound

This paper cites High-Throughput CNN Inference on Embedded ARM Big.LITTLE Multicore Processors,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms High-Throughput CNN Inference on Embedded ARM Big.LITTLE Multicore Processors,

Reference 19

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Observation 15535965-6b08-4a72-80d9-afc045456501 · outbound

This paper cites Easter: Learning to split transformers at the edge robustly,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Easter: Learning to split transformers at the edge robustly,

Reference 20

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 527b51dc-d979-4dca-ab91-765d590c741a · outbound

This paper cites Pipebert: High-throughput bert inference for arm big.little multi-core processors,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Pipebert: High-throughput bert inference for arm big.little multi-core processors,

Reference 21

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 939f13e8-31a3-4114-b547-eb3cfb99e861 · outbound

This paper cites Shared memory-contention-aware con- current dnn execution for diversely heterogeneous system-on-chips,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Shared memory-contention-aware con- current dnn execution for diversely heterogeneous system-on-chips,

Reference 22

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Observation 9bd31035-6d66-4d86-8205-2cd4fe6a9486 · outbound

This paper cites Mapformer: Attention-based multi-dnn manager for throughout & power co-optimization on em- bedded devices,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Mapformer: Attention-based multi-dnn manager for throughout & power co-optimization on em- bedded devices,

Reference 23

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Observation 5e8741f6-10e0-4a9d-810c-98df5fbfc41f · outbound

This paper cites Rknn toolkit operator support list (v1.7.5),.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Rknn toolkit operator support list (v1.7.5),

Reference 24

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6e9dd41d-63ad-4ff5-bc5a-b43d0ffee1ec · outbound

This paper cites Working with dla,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Working with dla,

Reference 25

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6c1a7737-8b7b-499c-856b-906b52cde40a · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 26

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Observation 9a1d5b15-ac93-4215-9bf5-6967766fa186 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2918453a-c478-4a73-b7db-a5c70c95926b · outbound

This paper cites Nvidia jetson Orin,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Nvidia jetson Orin,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation cee98bd5-9e34-4a1c-ad5e-f4ece495656f · outbound

This paper cites Interference-aware dnn serving on heterogeneous processors in edge systems,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Interference-aware dnn serving on heterogeneous processors in edge systems,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.481032Z digest=sha256:c5ce92d81e9a913f32cacde1a48e7826583af705bcf93944550085f6b580d344

Observation ca3b2c85-151a-4a6b-8c24-2ee78ea0becb · outbound

This paper cites Rankmap: Priority- aware multi-dnn manager for heterogeneous embedded devices,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Rankmap: Priority- aware multi-dnn manager for heterogeneous embedded devices,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.484228Z digest=sha256:82d30778dd36b6181428c796f3a59bb8c29f397bcd47a41e303f43b34c6ed808

Observation 83a81f5b-1c26-4f34-aede-6a48b8ba1e8f · outbound

This paper cites Energy-aware scenario-based mapping of deep learning applications onto heterogeneous processors under real-time constraints,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Energy-aware scenario-based mapping of deep learning applications onto heterogeneous processors under real-time constraints,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.487510Z digest=sha256:7943b1cc9770ad3aaa6b4784bfaa3a8209e04c7c07f98add2c17f8db12313dc8

Observation dafd13b2-8447-4f7d-9e20-70feca5cd3ff · outbound

This paper cites Axonn: Energy-aware execution of neural network inference on multi-accelerator heterogeneous socs,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Axonn: Energy-aware execution of neural network inference on multi-accelerator heterogeneous socs,

Reference 32

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.490158Z digest=sha256:c02b4250ba9c27327f5b6ab4808e317e0a31e2499938f18a7c4859f13313ef75

Observation 27e562af-b12d-43d9-bdbe-0d4ebfe9056e · outbound

This paper cites Onnx runtime,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Onnx runtime,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.493398Z digest=sha256:f6ddd279ea71c8b41ce56190957af29de205abcf1c8036cf9e46071413963066

Observation 40b53c34-2f54-4369-85cf-40d8802c4055 · outbound

This paper cites Gaussian error linear units (gelus),.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Gaussian error linear units (gelus),

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:20:29.496242Z digest=sha256:38237f768345fd9c4f7a4d1c2a16bee80e8a34a94e423a466a1e1d40fe78d37e

Observation 08bf4f45-3bea-4429-9841-aff7d91e37a5 · outbound

This paper cites Deep residual learning for image recognition,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Deep residual learning for image recognition,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T21:20:29.498955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:20:29.498955Z digest=sha256:9b151ab98be31ea66c302721a5f28056df1ef6e3ad4b8c4f95874cd34f835d8d

Observation 00098e68-b5a3-4a01-9e6b-0bb048db52b4 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Efficientnet: Rethinking model scaling for convolutional neural networks,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.736593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.502105Z digest=sha256:995a623e80e91b72cea878c8f2ec02f645a7652ce63633b56f2e6182a2f9d747

Observation dd1b138b-3259-4c89-a960-439f23ecd09f · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T21:20:29.505324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:20:29.505324Z digest=sha256:4275c92eba0ee53a9ccdc1485290621dd2727626467408c141d64f3845dad094

Observation 30d91ddd-38bb-414b-8bf9-01906c6e625e · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.724746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.508336Z digest=sha256:1e8fd92493e55db43fccb7db60408a6a7beb3de596bcf7401cafad00c6f7af84

Observation 16bab500-ab8b-43e6-ad43-91f46dbb1221 · outbound

This paper cites Pytorch installation guide,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Pytorch installation guide,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.713879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.511005Z digest=sha256:17be50139ffe4849dc34e60819f25beb3df6796fb0cbdf420b64475000944e9e

Observation 5dbd3ff7-798a-435a-adf5-d5b1557d7776 · outbound

This paper cites Torchvision,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Torchvision,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.703196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.514309Z digest=sha256:5416efe8a041705f32e0a1a932fdaf5c2f71b12ee2c7348cb05c5e327f185c19

Observation 800078de-c64c-4bde-9642-62c87642411d · outbound

This paper cites Hugging face: The ai community building the future of machine learning,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Hugging face: The ai community building the future of machine learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.692905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.517586Z digest=sha256:2c382437a24dc7d72c3c3ed40aadb055c486062a020a268cc6aac784e58156f4

Observation bf831979-547d-4f88-bad0-b3298ebd843f · outbound

This paper cites Ollama: Run large language models locally,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Ollama: Run large language models locally,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:20:29.680283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:20:29.520747Z digest=sha256:f52a4f0b7b8f7f633cf64061c854900abe4e34d188565851d529d302d5d24efe

Observation bb67abac-841b-453d-8b36-5344683c54f0 · outbound

This paper cites Gymnasium,.

Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms Gymnasium,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T21:20:29.524083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:20:29.524083Z digest=sha256:9898f9917be4a89553ceadb986939cb641d77e206132392bd042327abc31c7fc

Pith citing papers

No inbound Pith citation observations are available.