Paper Citation Record · LEDGER

A Survey of Resource-efficient LLM and Multimodal Foundation Models

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2401.08092.

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

pith.paper-citation-record.v1
2401.08092 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:39:39.101435Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T13:27:05.570944Z

Reference resolution

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verified exact0
verified fuzzy0
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External citation measurements

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Outbound references

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Pith citing papers

Observation 8dcab173-a130-4fb4-a797-53c2d55bd7cc · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 24

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Source-reported events for the cited work

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Observation c0c782cc-e23b-4340-be56-060838aeb10d · inbound

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs cites this paper.

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 3

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Observation bd33d71b-569c-40a2-92f3-b2bf96e3d562 · inbound

GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS cites this paper.

GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 40

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Observation a792b44a-257a-4084-9925-b4c5e412ffc9 · inbound

SoftmAP: Software-Hardware Co-design for Integer-Only Softmax on Associative Processors cites this paper.

SoftmAP: Software-Hardware Co-design for Integer-Only Softmax on Associative Processors A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 4

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Observation d54b971a-86f6-447b-9252-ccf5e3cc206f · inbound

DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users cites this paper.

DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 39

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Observation c06878f9-01fa-433a-8635-858066478ccb · inbound

A Survey on Inference Optimization Techniques for Mixture of Experts Models cites this paper.

A Survey on Inference Optimization Techniques for Mixture of Experts Models A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 198

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Observation fed14d4d-7139-467a-a0ce-7103a9291d4b · inbound

Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions cites this paper.

Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 225

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Observation 6228cef4-4dd2-4c59-a563-b9bd40c58774 · inbound

Efficiently Serving Large Multimodal Models Using EPD Disaggregation cites this paper.

Efficiently Serving Large Multimodal Models Using EPD Disaggregation A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 13

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Observation 196022ff-cf7d-4578-ba83-6afb1afda3c3 · inbound

Accelerating Large Language Models through Partially Linear Feed-Forward Network cites this paper.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 60

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Observation b9e7caa6-86aa-4b37-8f4f-ff12902a5223 · inbound

Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audio cites this paper.

Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audio A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 12

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Observation 029b37a1-2f72-40f2-9ba4-1120f9f55da0 · inbound

"It was Mentally Painful to Try and Stop": Design Opportunities for Just-in-Time Interventions for People with Obsessive-Compulsive Disorder in the Real World cites this paper.

"It was Mentally Painful to Try and Stop": Design Opportunities for Just-in-Time Interventions for People with Obsessive-Compulsive Disorder in the Real World A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 137

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Observation c116a34c-aef5-4539-a1a4-3d9219e25b8f · inbound

Diffusion Augmented Retrieval: A Training-Free Approach to Interactive Text-to-Image Retrieval cites this paper.

Diffusion Augmented Retrieval: A Training-Free Approach to Interactive Text-to-Image Retrieval A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 37

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Observation e0659a2c-8017-47c3-a434-522e4b0233ff · inbound

Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents cites this paper.

Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 41

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Observation f1eb31fe-5972-4e4e-a3b0-afc09a9ba513 · inbound

Every Software as an Agent: Blueprint and Case Study cites this paper.

Every Software as an Agent: Blueprint and Case Study A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 20

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Observation 244fa8ed-f574-4a48-bfe6-f9582d173742 · inbound

Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education cites this paper.

Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 119

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Source-reported events for the cited work

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Observation f14b5346-b03c-4a31-a30c-b1521795488e · inbound

Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline cites this paper.

Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T17:55:54.150115Z

Source-reported events for the cited work

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Observation 68b05412-62f4-4bfb-b1b3-8ccfb6bc6ecf · inbound

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models cites this paper.

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 32

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Observation fcfefc06-9bf6-4d1a-8b19-5dbf64150101 · inbound

GreenFactory: Ensembling Zero-Cost Proxies to Estimate Performance of Neural Networks cites this paper.

GreenFactory: Ensembling Zero-Cost Proxies to Estimate Performance of Neural Networks A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T21:39:39.101435Z

Source-reported events for the cited work

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Observation bfdff950-47b8-41fe-9355-9a698d9cc65b · inbound

EfficientLLM: Efficiency in Large Language Models cites this paper.

EfficientLLM: Efficiency in Large Language Models A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 277

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Source-reported events for the cited work

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Observation 33ce2435-327e-49b8-953f-09acee7540f3 · inbound

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques cites this paper.

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 6

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Observation 133627ea-1279-4455-8dca-f0656fd6bac1 · inbound

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem cites this paper.

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T16:29:12.134314Z

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Observation 6cc590e3-06ba-4504-ab41-600222fa13b9 · inbound

Federated Learning for Large-Scale Cloud Robotic Manipulation: Opportunities and Challenges cites this paper.

Federated Learning for Large-Scale Cloud Robotic Manipulation: Opportunities and Challenges A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T14:42:06.939057Z

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Observation 8634a380-f065-4035-8626-d2bc5811827e · inbound

Towards Experiment Execution in Support of Community Benchmark Workflows for HPC cites this paper.

Towards Experiment Execution in Support of Community Benchmark Workflows for HPC A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 136

Resolution: unresolved; no resolver link, observed 2026-08-06T11:57:01.844568Z

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Observation a1b4eedf-3672-460d-ae2b-7d03e8faaba4 · inbound

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code cites this paper.

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:01:55.874726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b79e625f-5dc8-4cea-b60b-b9ca5a9f0509 · inbound

Consiglieres in the Shadow: Understanding the Use of Uncensored Large Language Models in Cybercrimes cites this paper.

Consiglieres in the Shadow: Understanding the Use of Uncensored Large Language Models in Cybercrimes A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 158

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:59.630074Z

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Observation 0c1d5cb6-1d0f-4f23-ace0-65534da65aa6 · inbound

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference cites this paper.

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:06:52.172968Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41e3692d-a9a5-457d-aa0a-bce76edb6c3d · inbound

Toward Efficient Agents: Memory, Tool learning, and Planning cites this paper.

Toward Efficient Agents: Memory, Tool learning, and Planning A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 156

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Observation 1b007de2-75c1-42ee-bb5e-ccaab7d421bf · inbound

Understanding Rate-Distortion Performance in Distributed Transformer Inference cites this paper.

Understanding Rate-Distortion Performance in Distributed Transformer Inference A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T10:02:42.588064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 52282e88-a358-436f-b738-2c094495b046 · inbound

Understanding Rate-Distortion Performance in Distributed Transformer Inference cites this paper.

Understanding Rate-Distortion Performance in Distributed Transformer Inference A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 12

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Observation afece50d-7ffa-4a00-ae22-bf6db5703e71 · inbound

Understanding Rate-Distortion Performance in Distributed Transformer Inference cites this paper.

Understanding Rate-Distortion Performance in Distributed Transformer Inference A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 12

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Observation 1f48e20d-b722-48cb-baab-0ba3e1dfb121 · inbound

Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support cites this paper.

Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:28:39.002200Z

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Observation cd002b07-4abb-49e7-8364-81b3ecedf5cc · inbound

Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models cites this paper.

Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 2

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c61f062f-547f-4641-b317-b876547873c0 · inbound

Bilevel Optimization for Neural Architecture Search cites this paper.

Bilevel Optimization for Neural Architecture Search A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:34:21.990406Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e159424-92cc-431a-b415-5bf478534af2 · inbound

ELEVATE: Designing Human-Centered GenAI Virtual Tutors for Scalable and Inclusive Education cites this paper.

ELEVATE: Designing Human-Centered GenAI Virtual Tutors for Scalable and Inclusive Education A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-01T07:45:29.233849Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 721c1a7a-956f-42f5-8d2e-0c63b726a54c · inbound

Rethinking Small VLM Quantization: From Component-Wise Analysis to Hardware-Aware Edge Deployment cites this paper.

Rethinking Small VLM Quantization: From Component-Wise Analysis to Hardware-Aware Edge Deployment A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-10T13:27:05.572840Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 00bb3588-d8ba-44a9-a189-80e25a2821c8 · inbound

FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs cites this paper.

FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 66

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Observation d6ffad8b-2c7e-4e33-997d-4f4dd601b778 · inbound

LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs cites this paper.

LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:55:56.390091Z

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