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Paper Citation Record · LEDGER

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications

As of 7 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2507.21199.

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

pith.paper-citation-record.v1
2507.21199 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:26:26.336264Z

measured 64 of 64 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

64 of 64 outbound references displayed

  • verified exact0
  • verified fuzzy59
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21d78f95-1c11-4270-80bf-c715b177592e · outbound

This paper cites A review on methods and applications in multimodal deep learning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications A review on methods and applications in multimodal deep learning,

Reference 1

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verified fuzzy
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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 601d8447-8332-4894-b01e-702a3f063228 · outbound

This paper cites On the Road with GPT-4V (ision): Explorations of Utilizing Visual-Language Model as Autonomous Driving Agent,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications On the Road with GPT-4V (ision): Explorations of Utilizing Visual-Language Model as Autonomous Driving Agent,

Reference 2

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verified fuzzy
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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 6e9b198c-a10e-46ff-8079-2ae2a65ce621 · outbound

This paper cites 6G-Enabled Network in Box for Internet of Connected Vehicles,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications 6G-Enabled Network in Box for Internet of Connected Vehicles,

Reference 3

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verified fuzzy
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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 b8559427-458f-44f7-a649-72ca0e5ef1df · outbound

This paper cites LLM Enhanced Reconfigurable Intelligent Surface for Energy-Efficient and Reliable 6G IoV,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications LLM Enhanced Reconfigurable Intelligent Surface for Energy-Efficient and Reliable 6G IoV,

Reference 4

Resolution
verified fuzzy
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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 4818d69b-4d2f-4b7c-8f05-5be1290c895c · outbound

This paper cites A UA V-Assisted Secure Communication System by Jointly Optimizing Transmit Power and Trajectory in the Internet of Things,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications A UA V-Assisted Secure Communication System by Jointly Optimizing Transmit Power and Trajectory in the Internet of Things,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.976353Z

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 840d9aad-9cc2-4083-8648-fea26be8d8fe · outbound

This paper cites an unresolved cited work.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T13:26:27.966581Z

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 2063cac5-45a3-40d5-8c64-bf8a63d7aa5a · outbound

This paper cites Possible Applications of Sixth Generation Communication Networks,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Possible Applications of Sixth Generation Communication Networks,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.956698Z

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 5fcfc3be-4228-491a-a39b-23167176e09e · outbound

This paper cites Mining KPI correlations for non-parametric anomaly diagnosis in wireless networks,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Mining KPI correlations for non-parametric anomaly diagnosis in wireless networks,

Reference 8

Resolution
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raw_fallback, observed 2026-08-06T13:26:27.945981Z

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=2026-08-06T13:26:21.727608Z digest=sha256:fe9e44f646bf7594f1157de14eaac5d0482dc3780d4ba0e74b511137f5fda48e

Observation f19541ab-f2fe-476f-8e82-65675ddcd72f · outbound

This paper cites A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning,

Reference 9

Resolution
verified fuzzy
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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=2026-08-06T13:26:21.779993Z digest=sha256:44025c92bc7d33e2bf97f708f5e838a8bbc41132ad1d0c3d7348924af44e5c8b

Observation 16a6e877-1514-4567-b8ec-a77118015199 · outbound

This paper cites 6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications 6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities,

Reference 10

Resolution
verified fuzzy
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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=2026-08-06T13:26:21.869780Z digest=sha256:e626e50ab22d793949f43daea6ec5bcff9dbade7b38440e399f9e1be1dc48057

Observation 5cf81d7b-bdc8-4cd8-916b-a8f6aec1618b · outbound

This paper cites The Roadmap to 6G: AI Empowered Wireless Networks,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications The Roadmap to 6G: AI Empowered Wireless Networks,

Reference 11

Resolution
verified fuzzy
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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=2026-08-06T13:26:21.946897Z digest=sha256:7d3c60ac5856adaae50481e0faf0091a455f353dfa8a38e22c8693f8d5b85eec

Observation 8ec84ed3-5590-46c3-bbb3-60aa4bf1dbdb · outbound

This paper cites Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.906602Z

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 c0886c7c-2848-4dcd-8b9e-938339c47af2 · outbound

This paper cites Survey on the Internet of Vehicles: Network Architectures and Appli- cations,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Survey on the Internet of Vehicles: Network Architectures and Appli- cations,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.897287Z

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=2026-08-06T13:26:22.098136Z digest=sha256:696efe906bab47193b468bef3bbfb579806aefeb5ee93d0e8c40dcfd1065ff64

Observation 0b78bbab-8b8c-4e9d-83d4-fa10f125aae4 · outbound

This paper cites Uncovering what, why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Uncovering what, why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.888099Z

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 bd2187ea-87cf-43b8-8bfb-afe996888ed6 · outbound

This paper cites An LLM-Based vision and Language Cobot Navigation Approach for Human-Centric Smart Manufacturing,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications An LLM-Based vision and Language Cobot Navigation Approach for Human-Centric Smart Manufacturing,

Reference 15

Resolution
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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 0fd9e2ee-dd68-492b-8137-d78e150ef3b2 · outbound

This paper cites The smart factory as a key construct of industry 4.0: A systematic literature review,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications The smart factory as a key construct of industry 4.0: A systematic literature review,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.868036Z

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 b0cd7bc0-b8fd-4065-82f1-c949b5105b87 · outbound

This paper cites Artificial Intelligence Computing for a Smart City, G-Enabled Network in Box for Internet of Connected Vehicles,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Artificial Intelligence Computing for a Smart City, G-Enabled Network in Box for Internet of Connected Vehicles,

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T13:26:27.858700Z

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 75d68a8e-a1bc-4cac-b714-0c899ce178d3 · outbound

This paper cites Semisu- pervised deep reinforcement learning in support of IoT and smart city services,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Semisu- pervised deep reinforcement learning in support of IoT and smart city services,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.849013Z

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 0e0f055f-6b2d-4db5-bf52-fdf67663858e · outbound

This paper cites Cross-Task Multimodal Reinforcement for Long Tail Next POI Recommendation,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Cross-Task Multimodal Reinforcement for Long Tail Next POI Recommendation,

Reference 19

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raw_fallback, observed 2026-08-06T13:26:27.838952Z

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=2026-08-06T13:26:22.503216Z digest=sha256:48f8874cd2c2e45b2044c06f5d861bb168ba67b07643bc04c090182de7f52d74

Observation 3d15a7bb-28c1-4793-9e24-81f734214213 · outbound

This paper cites Multi-modal Knowledge-aware Reinforcement Learning Network for Explainable Recommendation,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Multi-modal Knowledge-aware Reinforcement Learning Network for Explainable Recommendation,

Reference 20

Resolution
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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=2026-08-06T13:26:22.565630Z digest=sha256:e5067e9e1b03077c7cd3fd0f8ec32c106a6817c3d9922e73b6efa35fc01d685c

Observation 093e4af8-bcb5-423f-830a-e3ad1ea4905d · outbound

This paper cites A Hierarchical Hybrid Learning Framework for Multi-Agent Trajectory Prediction,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications A Hierarchical Hybrid Learning Framework for Multi-Agent Trajectory Prediction,

Reference 21

Resolution
verified fuzzy
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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=2026-08-06T13:26:22.639028Z digest=sha256:4b0b175b33bedd20575d9bfc64943d100e642da4bc28cf517fa8c8b0f2088252

Observation 670f7347-804a-4e5c-a67c-4c57b6021b26 · outbound

This paper cites Inter- active Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Inter- active Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning,

Reference 22

Resolution
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raw_fallback, observed 2026-08-06T13:26:27.811629Z

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 2d944246-c4ad-4012-ab62-5f8da3857c9b · outbound

This paper cites Multimodal Large Language Models: A Survey,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Multimodal Large Language Models: A Survey,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.801974Z

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=2026-08-06T13:26:22.754988Z digest=sha256:f20942d9c597b256788e6ac487bd6be176c88d961262cb4ca63cc3cff715d9ca

Observation a4ce3374-e8c5-493d-b8b6-bb90b1402288 · outbound

This paper cites NExT-GPT: Any-to-Any Multimodal LLM,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications NExT-GPT: Any-to-Any Multimodal LLM,

Reference 24

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raw_fallback, observed 2026-08-06T13:26:27.792259Z

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=2026-08-06T13:26:22.843693Z digest=sha256:2a53246347a829d5835711a06ea49ea77a1efd6b2592f4abff344dfb767fbb63

Observation 52ac4d03-fe4d-4990-bb6b-ae9e3dc16f97 · outbound

This paper cites Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry, and Fusion,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry, and Fusion,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.782383Z

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=2026-08-06T13:26:22.908054Z digest=sha256:9e0ad9e03ab3910b5112c1407bdd63e86ff931d90efec70af87dddbbc08f9869

Observation a11688d6-c409-40c9-8964-eccf92d886f1 · outbound

This paper cites Reparameterized Policy Learning for Multimodal Trajectory Optimization,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Reparameterized Policy Learning for Multimodal Trajectory Optimization,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.771712Z

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=2026-08-06T13:26:22.996863Z digest=sha256:936da0be7d297bf5cb939daa9507ef208c924c6b0431e519fbdedab4d86983b4

Observation 5329587b-a68d-427d-9232-4994e4a90e8a · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications LoRA: Low-Rank Adaptation of Large Language Models,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.760573Z

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=2026-08-06T13:26:23.073040Z digest=sha256:58379e601aee730aef060c77ceaafde620ee08b4ba1b1c45449fc9f81d8e821c

Observation abcd2cfd-b75a-405e-9aa5-ccac2553c4c8 · outbound

This paper cites Mixture-of-Experts with Expert Choice Routing,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Mixture-of-Experts with Expert Choice Routing,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.751263Z

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=2026-08-06T13:26:23.152083Z digest=sha256:ff07269b0a2885b3fdf99e871d7a9e145317dd45b9c71309c2b55f30f8cb628c

Observation fc6839c4-638d-4f10-9989-100dd83ec759 · outbound

This paper cites Data Quality- Aware Task Offloading in Mobile Edge Computing: An Optimal Stop- ping Theory Approach,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Data Quality- Aware Task Offloading in Mobile Edge Computing: An Optimal Stop- ping Theory Approach,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.740629Z

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=2026-08-06T13:26:23.211305Z digest=sha256:76335113d1d0e912e8441c5b016019d00a9f67c5d592b13b5e0635d409c865f0

Observation 4b70f9bc-8721-4bfc-9073-7e33e6b90a03 · outbound

This paper cites Consumer Privacy Concerns about Internet Marketing,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Consumer Privacy Concerns about Internet Marketing,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.729487Z

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=2026-08-06T13:26:23.301840Z digest=sha256:7ec0ebb8810f8b62f19f0f2d6c96a5d26cdd10f799f529fce0a99b63e5af3977

Observation d79354f5-1cfb-4629-88fd-f7b90d919170 · outbound

This paper cites Towards QoS-aware provisioning of chained virtual security services in edge networks,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Towards QoS-aware provisioning of chained virtual security services in edge networks,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.719169Z

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=2026-08-06T13:26:23.358420Z digest=sha256:230eb60eeba54e143745018d4eeef09a68b41814b3f4e5a0f9c7a90a0e8aac0e

Observation 4b6c3fb6-ae02-4b50-b6d6-69664e13a2af · outbound

This paper cites Mixture of experts: a literature survey,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Mixture of experts: a literature survey,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T13:26:23.429040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:26:23.429040Z digest=sha256:6ae4a7b9fe3e3a36aae62f79f0ad251a05adb225abbedf1137f18bda0b3f6297

Observation c8086d1b-aa72-4fa4-b0b8-70aa97fec8c7 · outbound

This paper cites TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition

Reference 33

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unresolved
no resolver link, observed 2026-08-06T13:26:23.494874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:26:23.494874Z digest=sha256:0bdebbd5bff56f1b688fb5494187170c7ca716b1fbc206cabd956bee6459f8fa

Observation 29bd2067-a7fe-4362-8076-74eba3b6f7a0 · outbound

This paper cites MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.702400Z

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=2026-08-06T13:26:23.586196Z digest=sha256:998a6add2333acc3801d6957755a3af4a341f18dcade9e04429fb7764b868f65

Observation d7cd87e2-28bf-4ec2-bacb-5d4af0cd9560 · outbound

This paper cites Seeded LoRA: Collaborative Fine-Tuning Through Seed Initialization of Adapters,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Seeded LoRA: Collaborative Fine-Tuning Through Seed Initialization of Adapters,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.692566Z

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=2026-08-06T13:26:23.678025Z digest=sha256:10d1924363e955c077559600baf671aa702cf2cb1f8d62ffc2d910eb00b72f37

Observation 108b27e7-1975-4f3d-9c1c-3a3bffc87925 · outbound

This paper cites Learning to Route Among Specialized Experts for Zero-Shot Generalization,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Learning to Route Among Specialized Experts for Zero-Shot Generalization,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.682618Z

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=2026-08-06T13:26:23.757290Z digest=sha256:2c950e943e03faf2413700f7baaf12f0d3c1c0c9b9010eb3e40b6c8abf006f69

Observation 6d01f9c8-1ae2-4ca6-9349-47ee544ce76b · outbound

This paper cites LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T13:26:23.796419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:26:23.796419Z digest=sha256:a3cbf384496635c9ae16e9c568e0551f33bb348d387ef10e71cc721ce88d9d39

Observation 7de90692-cc27-400c-aebd-64695ea19ad4 · outbound

This paper cites Towards Modular LLMs by Building and Reusing a Library of LoRAs,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Towards Modular LLMs by Building and Reusing a Library of LoRAs,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.672977Z

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=2026-08-06T13:26:23.884685Z digest=sha256:79342349898b76c858845fb6b7a583452230a0ca31e09b56b9556221d65589e6

Observation 9471b00f-96d1-4d67-b5a7-12dedf98cf80 · outbound

This paper cites LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition,

Reference 39

Resolution
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raw_fallback, observed 2026-08-06T13:26:27.662580Z

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=2026-08-06T13:26:23.987821Z digest=sha256:ce3e7bea56b43a1530924cd982ba800f7f960a00874166cdfe6fcad6e20cee39

Observation 40c5237c-2fce-4a4d-a68a-3c21e961ef8a · outbound

This paper cites Swarm Par- allelism: Training Large Models Can Be Surprisingly Communication- Efficient,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Swarm Par- allelism: Training Large Models Can Be Surprisingly Communication- Efficient,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.652651Z

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=2026-08-06T13:26:24.046530Z digest=sha256:7b9938898cb4a05e452eb3d5b736b5590337730134764c920831476a744d478d

Observation 87fa37f1-c021-4eb8-837f-07d5dfe4d9fa · outbound

This paper cites PyTorch Dis- tributed: Experiences on Accelerating Data Parallel Training,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications PyTorch Dis- tributed: Experiences on Accelerating Data Parallel Training,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.642904Z

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=2026-08-06T13:26:24.090348Z digest=sha256:8f01b64dc7e55148c2ac2a4bae2871e47464f70a64333333d1ac555abfda4468

Observation ca3ac8af-116d-443e-93f2-ac09dca9136d · outbound

This paper cites Petuum: A New Platform for Distributed Machine Learning on Big Data,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Petuum: A New Platform for Distributed Machine Learning on Big Data,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.632504Z

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=2026-08-06T13:26:24.198089Z digest=sha256:b98a25a6c41b250f6804f5bef8207a16b8d96fae76f148c0364286ea51377886

Observation 07739194-0c37-4ea7-b731-6c62fdc7f804 · outbound

This paper cites Tesseract: Parallelize the Tensor Parallelism Efficiently,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Tesseract: Parallelize the Tensor Parallelism Efficiently,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.622969Z

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=2026-08-06T13:26:24.280660Z digest=sha256:f42930fbca072a7a2cfdbe6112b46aeae036d1aee458658514bf0db3b1931f17

Observation 8e8581fb-ffe0-40b3-aadf-60b35cf46953 · outbound

This paper cites GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.613371Z

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=2026-08-06T13:26:24.354787Z digest=sha256:ced11a2f3158132acdea792951a5059a71c358cdd9e1ab536cb054fd6aa9d19c

Observation 0da26045-f04b-4df5-a989-7e18e2cd7a6f · outbound

This paper cites PipeMare: Asynchronous Pipeline Parallel DNN Training,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications PipeMare: Asynchronous Pipeline Parallel DNN Training,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.604496Z

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=2026-08-06T13:26:24.464039Z digest=sha256:77683ad78616e69b461c2bbc17b7ad32caf79f76f56a855081ffd6b2ddb215f7

Observation 7689b90c-251e-40c5-8c86-08598f004257 · outbound

This paper cites TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.595434Z

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=2026-08-06T13:26:24.524884Z digest=sha256:fc02b937c10f45d60b94bd40fbe3a9b87db930d2350c4fca83fb7daeecb3f8fd

Observation d37e0405-befd-4783-91c3-46adae678f31 · outbound

This paper cites A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.586532Z

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=2026-08-06T13:26:24.576776Z digest=sha256:36a8aca0784fb85a660b453dd3d6d07d1f5eb2ec03a9e49836447bef6fe23587

Observation 1cf4f65d-9fe8-431f-a8d5-2867607142a9 · outbound

This paper cites HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.577603Z

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=2026-08-06T13:26:24.703299Z digest=sha256:16cb9aecdf7f7ecefbd1b127dcf6e1edde66a302d6737c6194a6e9d9c4177ee2

Observation da863b49-1f8e-4656-be02-e155defaecea · outbound

This paper cites PipeDream: Generalized Pipeline Parallelism for DNN Training,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications PipeDream: Generalized Pipeline Parallelism for DNN Training,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.568724Z

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=2026-08-06T13:26:24.802081Z digest=sha256:df15fd282a8633bad9ebdedfa86824969280d8e9797b027959ab3fdf79f306c5

Observation 79abfd3e-f7d7-495a-86bb-72fbfc52aa8b · outbound

This paper cites Visual Instruction Tuning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Visual Instruction Tuning,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.559825Z

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=2026-08-06T13:26:24.908860Z digest=sha256:3005801c49e5d6f16dfdc784dc0b772aa99eb2516d35be94ede1e5919d20784b

Observation 9e52637e-ea97-4b5f-bca6-53d412355b8a · outbound

This paper cites HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T13:26:24.994164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:26:24.994164Z digest=sha256:1b2f9e26c760114f76e508ca7e1fa3284d66b435d1d0f5a97c1908931296593b

Observation 20dfb8ad-b4b0-4ed1-8d46-c9f33c94495f · outbound

This paper cites Mixture of LoRA Experts,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Mixture of LoRA Experts,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.551292Z

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=2026-08-06T13:26:25.079047Z digest=sha256:9e23119b3de1e1761f014f67466f6260ebcbff3676b1bfac1eace78d0b2fd1e7

Observation 1b639c4c-4657-4717-b7ce-9be58917a975 · outbound

This paper cites JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.541847Z

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=2026-08-06T13:26:25.182147Z digest=sha256:e4e8cdc9594decbd5561f3569cce0ff2973b8af078bdfc7ad534fdb0aab9d4bf

Observation d42a807b-3dac-4455-bbdc-1ec4fff65d21 · outbound

This paper cites ZeRO: Memory Optimizations Toward Training Trillion Parameter Models,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications ZeRO: Memory Optimizations Toward Training Trillion Parameter Models,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.531547Z

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=2026-08-06T13:26:25.259792Z digest=sha256:fa77d33183ea6f4954e559d41cf91c8abf0d3e03175f91dd3ab9e748dae25d99

Observation b9642d64-219e-4108-8213-40e32fbe7405 · outbound

This paper cites Wireless Sensor-Based Traffic Light Control,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Wireless Sensor-Based Traffic Light Control,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.521147Z

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=2026-08-06T13:26:25.364613Z digest=sha256:dc7fba5169425190c83fadad3544fc83f5e3b17a8f5dbff83ac26b8e762c8532

Observation 2b9b6b37-9d27-4502-b32d-4a3c6596bf18 · outbound

This paper cites Tactile Internet for Autonomous Vehicles: Latency and Reliability Analysis,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Tactile Internet for Autonomous Vehicles: Latency and Reliability Analysis,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.511719Z

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=2026-08-06T13:26:25.472724Z digest=sha256:5886b11aa8cda3a9ae1ac803d25d207fed70d66fec0933774cfdcaecf863b01d

Observation 7b208185-0af7-4b51-9bfb-ff3b16f7622a · outbound

This paper cites Energy-Aware AI- Driven Framework for Edge-Computing-Based IoT Applications,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Energy-Aware AI- Driven Framework for Edge-Computing-Based IoT Applications,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.502567Z

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=2026-08-06T13:26:25.590055Z digest=sha256:e2f07ad58a2aca4a3b5498644223a6a446c3bb5c471012bea5bbbbfef5c8c553

Observation 93c85537-dd83-4cdd-a082-c63f5a75d6af · outbound

This paper cites Vision-Aided Ultra-Reliable Low-Latency Communications for Smart Factory,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Vision-Aided Ultra-Reliable Low-Latency Communications for Smart Factory,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.493780Z

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=2026-08-06T13:26:25.669149Z digest=sha256:61e4242861db6aa97671682f10461eab7cbbae11fafa3ebe6c90821b1e9235d4

Observation ba3584a7-6b00-4da2-8fec-753ab5e283ac · outbound

This paper cites Edge Computing for Autonomous Driving: Opportunities and Challenges,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Edge Computing for Autonomous Driving: Opportunities and Challenges,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.483359Z

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=2026-08-06T13:26:25.760472Z digest=sha256:fb343031e024d7dba521277d63cf2b8a91ab776260d78d422424090f0bd1a77d

Observation cac8eff8-c769-4eb0-8c6b-fd74e3393831 · outbound

This paper cites Elastic Urban Video Surveillance System Using Edge Computing,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Elastic Urban Video Surveillance System Using Edge Computing,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.471718Z

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=2026-08-06T13:26:25.893401Z digest=sha256:a8cffe10001c0d9d3ea5424c85df69919a9dac28c94608a4a29998618ce15746

Observation b585be48-cd61-4593-ab4b-dfb4cfc429a2 · outbound

This paper cites Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.393416Z

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=2026-08-06T13:26:25.966851Z digest=sha256:787f1df517514eb72e117f1b8a6cd817e940b50dd492508a8877ec7c4f38e82d

Observation 71fe1e82-51ca-414c-9205-edb3786bc7bb · outbound

This paper cites FedFMSL: Federated Learning of Foundations Models With Sparsely Activated LoRA,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications FedFMSL: Federated Learning of Foundations Models With Sparsely Activated LoRA,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:27.076542Z

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=2026-08-06T13:26:26.135802Z digest=sha256:f99fa6611a81030f5afb02def6b6e786aeeabf596a347ee21e7bdfe55cbcb009

Observation f14edd84-65a1-4113-996a-1e2313f6dbca · outbound

This paper cites Het- erogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications Het- erogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:26.790613Z

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=2026-08-06T13:26:26.211598Z digest=sha256:551a4fc18d9b42bb642409e25d3a26fe37fa35de938f06eb559ec554e7cc7fb9

Observation 941773b7-958a-4c15-be13-799650b05a89 · outbound

This paper cites FedFMSL: Federated Learning of Foundation Models With Sparsely Activated LoRA,.

Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications FedFMSL: Federated Learning of Foundation Models With Sparsely Activated LoRA,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:26:26.583117Z

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=2026-08-06T13:26:26.336264Z digest=sha256:3cf9c38c5dd083635700bdcbaf3e85493db2ec63820937934486eb92a1df5eff

Pith citing papers

No inbound Pith citation observations are available.