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Paper Citation Record · LEDGER

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2507.11515.

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

pith.paper-citation-record.v1
2507.11515 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:16:11.555301Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:16:05.343599Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:16:12.878356Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact3
  • verified fuzzy32
  • unresolved13
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7f9bda2-8304-49f1-889e-f0a347b3eff8 · outbound

This paper cites , L} contains a self-attention (SA) block and an FFN block.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air , L} contains a self-attention (SA) block and an FFN block

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:20.234591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.605746Z digest=sha256:8d041dbdaa41e866bd628ff99d5285f39d125f1c0bb8aee6f205334f7a4d1657

Observation 43d3a04a-42d7-48cf-b890-79bc9dedd02c · outbound

This paper cites an unresolved cited work.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Unresolved cited work

Reference 2

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unresolved
raw_fallback, observed 2026-08-06T17:16:20.065567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.714041Z digest=sha256:5019bfd28280d6f9322fc26b12c27521d71182cbc14fc72b81eacd822b43da00

Observation 79e705de-899f-4553-a5e2-228fa6413e6b · outbound

This paper cites an unresolved cited work.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Unresolved cited work

Reference 3

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raw_fallback, observed 2026-08-06T17:16:19.360685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.211740Z digest=sha256:7934f487c07e4179a1e31ce734249f07af10252b6c5e9e24dd610b41d7bf0b43

Observation 95ca019a-dbf4-4475-a06f-f54cd7f2a08d · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 4

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unresolved
no resolver link, observed 2026-08-06T17:16:06.881395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:06.881395Z digest=sha256:3f711182118e9110aa7d83f64f0feff6313a2209aa2e548d8234bd831db2f7c2

Observation 1795a6ec-6e82-495d-a5a4-2b252c3c3ff2 · outbound

This paper cites To enable adaptive rank configuration under real-world constraints such as wireless bandwidth and task complexity, we formulate the rank allocation as an MDP (S, A, R).

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air To enable adaptive rank configuration under real-world constraints such as wireless bandwidth and task complexity, we formulate the rank allocation as an MDP (S, A, R)

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:19.942746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.822179Z digest=sha256:a5c1155e60746662019b73429b177f05df03b83ba4a549a06206e50cf3b157bc

Observation c39a2e92-f70d-4cf4-aefe-52c7ac3f7dc2 · outbound

This paper cites AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T17:16:13.002009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.343599Z digest=sha256:b0d48dff2fe2b15efd5766123a5d11e011f8789c94a9846a34511c6848f0ab7d

Observation 266bd7e0-6280-4b65-ba3e-242f063bc3f9 · outbound

This paper cites Beforehand, we briefly present the key ingre- dients related to PPO.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Beforehand, we briefly present the key ingre- dients related to PPO

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:19.828781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.960017Z digest=sha256:699894bb59c1f3e616d8a3b33a3846b09404605378ee2b5879a3899c3f6a692f

Observation e30eee6a-d37f-400d-9192-62834571984e · outbound

This paper cites Notably, DDIM shares the same training objective and noise schedule as DDPM, with the main distinction residing in the sampling procedure used during inference.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Notably, DDIM shares the same training objective and noise schedule as DDPM, with the main distinction residing in the sampling procedure used during inference

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:19.690043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.079245Z digest=sha256:391aba8a4e3a48ace145c61b001609f723f6be0f0e30afcce4865baa5df16db8

Observation bbbff032-7f88-4f71-a1b6-e355fcd9c73d · outbound

This paper cites an unresolved cited work.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Unresolved cited work

Reference 9

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unresolved
raw_fallback, observed 2026-08-06T17:16:19.559729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.149294Z digest=sha256:d0c0d28713439a9117f4e47997f10964877d9c72f48d526ca77074e23bb5edae

Observation edc21c4e-67df-4484-93fc-90a7a19dd0d1 · outbound

This paper cites Pre-trained models for natural language processing: A survey,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Pre-trained models for natural language processing: A survey,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.774007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:08.365793Z digest=sha256:20c4d2b419a07b16b0f2d910809c8c60f5d1aeb5a9eb77e63412d25724f7504d

Observation 953734cc-a0a9-46d8-bad1-4bf37a0ad080 · outbound

This paper cites Notably, we also study the performance differences when using MLP and U-Net as backbones of DDIM.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Notably, we also study the performance differences when using MLP and U-Net as backbones of DDIM

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:18.996618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.402698Z digest=sha256:b4c2bd8cdd7c2c7460d83f9a09d1c988ccfbdaf5f07eda2996d5be3d7bae73dc

Observation 1b97583e-cf19-48b0-8ad8-964a5736c983 · outbound

This paper cites (10), regulates the trade-off between task accuracy and communication cost.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air (10), regulates the trade-off between task accuracy and communication cost

Reference 12

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malformed identifier
raw_fallback, observed 2026-08-06T17:16:18.772232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.469247Z digest=sha256:5dba9817f8c6cf5165b6a7e06fc63c23041dc1296f34a23ca1eaff93432ab8f8

Observation 5f97ed12-5e3d-48c0-8f9c-9ef466dedd22 · outbound

This paper cites GPT-4 Technical Report.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air GPT-4 Technical Report

Reference 13

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unresolved
no resolver link, observed 2026-08-06T17:16:06.543831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:06.543831Z digest=sha256:85240bc291c818da7a0f1da03faaa6855e9e90f0cdb4a564baec26e68f42b42a

Observation bf2daecf-fb74-463e-9a66-c2474bb853d6 · outbound

This paper cites The proposed RL agent observes both data and channel state information [15] and dynamically adjusts rank budgets to balance model accuracy and transmission cost.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air The proposed RL agent observes both data and channel state information [15] and dynamically adjusts rank budgets to balance model accuracy and transmission cost

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:20.385922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.464684Z digest=sha256:6c7269c7522dd1bd76ed841e77fe18ed969472d8f98f5cfb1474c22e7a545348

Observation 756d4776-3a9d-4b19-9597-c62f4b6acba0 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:06.604190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:06.604190Z digest=sha256:2b72c9fc009f8f1079c8459548c881e77317254f403b54483692bb37b2b3bd0a

Observation 5115d334-46ec-433a-b08c-00ee9b438b70 · outbound

This paper cites Denoising diffusion probabilistic models,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Denoising diffusion probabilistic models,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.003281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.381682Z digest=sha256:1ae71013ff86f8a0fb79ce393908d62aecfe6638784b06add175ec7fd6d76022

Observation d44c2ab6-0775-4026-9ef3-b0341c28f436 · outbound

This paper cites LoRA: Low-Rank adaptation of large language models,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air LoRA: Low-Rank adaptation of large language models,

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:18.632874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.996776Z digest=sha256:0199fe212f22b60f725949cef91264458f515579f4e5353f01c0e6cc6aaafda8

Observation 812ba323-4c15-4e71-b54b-fe153ddfe691 · outbound

This paper cites AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:18.472683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:07.133478Z digest=sha256:3846902e8bbaec4375e1763c4e01b49c558b272ee90d92e3d81ef4a019e26dca

Observation 45c34858-2595-4fee-b2b1-97fedd5d4cff · outbound

This paper cites Adaptation in cloud resource configuration: a survey,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Adaptation in cloud resource configuration: a survey,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:18.230174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:07.277296Z digest=sha256:7bf4f1f9a3661fc26f648bc15904f9184e24f17bedcc5337dbd96097802e1120

Observation 988082b8-e4d1-4f83-9583-5fc31ceffbc3 · outbound

This paper cites Curriculum learning for natural language understanding,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Curriculum learning for natural language understanding,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:18.079384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:07.595195Z digest=sha256:9f19e251c66af5b6af031189da5b1c6d4300e93618ea465fb267e6f68107d17e

Observation 4bae311e-14a4-4428-b5f7-fb2e4a09194e · outbound

This paper cites Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding,

Reference 22

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raw_fallback, observed 2026-08-06T17:16:17.950661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:07.977388Z digest=sha256:d01e222f8e55a3f0573bdf9ef9c7a31f276fab74c05239272e6d72619ed3489a

Observation f8cec137-091a-484b-88af-5efc87064aa7 · outbound

This paper cites Goldsmith, Wireless Communications.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Goldsmith, Wireless Communications

Reference 23

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unresolved
no resolver link, observed 2026-08-06T17:16:09.930257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:09.930257Z digest=sha256:ac09de3f963dbb7f72116a5fb1bc069d3a2eec88659f62e98520082996ef7833

Observation d07ec172-5ece-4d79-b681-c57003b491e4 · outbound

This paper cites Channel characteristics and transmission performance for various channel configurations at 60 GHz,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Channel characteristics and transmission performance for various channel configurations at 60 GHz,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.646840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:08.512940Z digest=sha256:93a845947ec3445c4f449255713ae6b605020370fb858024fbc2f68fa7ec9d9b

Observation 1d03d688-1c3b-4003-b514-26b98560fe44 · outbound

This paper cites Feed-forward neural networks,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Feed-forward neural networks,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.548503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:08.606230Z digest=sha256:a293cb7e2cde750f7ea78c8738c969f0bee7addcaef6a57a0ef34f7f14017a92

Observation 33e0c77e-7ed9-4fed-bf64-70c49b6bc909 · outbound

This paper cites Real-time millimeter-wave MIMO channel sounder for dynamic directional me- asurements,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Real-time millimeter-wave MIMO channel sounder for dynamic directional me- asurements,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.420834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:08.752272Z digest=sha256:ad78ce1c12d1ab07672ee9e6aac4ce931e9d61bd4d35299d337f4a2a982f43b2

Observation 7ebe62f1-dec9-4804-94b2-b4bed1cea88b · outbound

This paper cites Szepesvári, Algorithms for reinforcement learning.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Szepesvári, Algorithms for reinforcement learning

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.298157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.026093Z digest=sha256:78f4af676f114ad925ed438d4b2d8ef15d39e48b3a61e445f90c15bf0d2f8f3e

Observation 2c5189a4-0fad-483e-a77f-9de340706dd8 · outbound

This paper cites Adaptive Sampling and Joint Semantic-Channel Coding under Dynamic Channel Environment.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Adaptive Sampling and Joint Semantic-Channel Coding under Dynamic Channel Environment

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:16:12.646887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.204441Z digest=sha256:8a5e9624e0a7c729f6d592981798a12400a1a6b4af55f41c67e12010897263bc

Observation b0511c08-ab02-41f3-b0a0-c8ce97422596 · outbound

This paper cites Diffusion policy policy optimization,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Diffusion policy policy optimization,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-06T17:16:17.162924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.276312Z digest=sha256:d8b2cd820c2d7899335f30fa8e177fe4b7a83301b1601cf3a4a728be98d5791f

Observation 8db297d4-7712-4450-b424-0526df3f426f · outbound

This paper cites Deep reinforcement learning that matters,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Deep reinforcement learning that matters,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:15.172844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.715728Z digest=sha256:268eff98c40216551749074066f5d90d278dffc272a087b760195e73acaaac1c

Observation 5b892ed9-8e3b-487b-a8fb-39d221d836fd · outbound

This paper cites Denoising diffusion implicit models,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Denoising diffusion implicit models,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:16.799510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.464284Z digest=sha256:9d1c012e629e2510f614167ed8968ad489e54b14511218ba0efe2ce97169e338

Observation 9b6dfb2d-78a4-40b5-999c-a710d56136af · outbound

This paper cites Proximal Policy Optimization Algorithms.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Proximal Policy Optimization Algorithms

Reference 32

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unresolved
no resolver link, observed 2026-08-06T17:16:09.543790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:09.543790Z digest=sha256:1dbbc7865b3647f5501c68ca3680883e9e8ce4f74f688219e773c05087692a1b

Observation 455931c1-97c7-462b-8c98-7a44ce5ac518 · outbound

This paper cites PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:16:12.303724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.645314Z digest=sha256:da4a9cf79de5f815ffdb4db43245faa1d6345fe0591510b6d258bab55e840c07

Observation cac3dffa-dbef-407d-90d2-56a66587c51f · outbound

This paper cites Wireless com- munication is modeled as an AWGN channel with 100 MHz bandwidth, 1s latency, and SNR levels ranging from −5 dB to 15 dB.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Wireless com- munication is modeled as an AWGN channel with 100 MHz bandwidth, 1s latency, and SNR levels ranging from −5 dB to 15 dB

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:19.161570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:06.299159Z digest=sha256:c3969903319ac784f57f77b548fe065954752f60678fce0a19f3a47526abfb8f

Observation dc4a2601-b025-4c0c-8fab-60af61479fd4 · outbound

This paper cites Intelligent cloud-edge collaborations assisted energy-efficient power control in heterogeneous networks,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Intelligent cloud-edge collaborations assisted energy-efficient power control in heterogeneous networks,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:16.593111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.742087Z digest=sha256:fcf8bae8103655dd157b6693e073ae59aaeecd3169c4e4380331add309e73d52

Observation 94596ae4-6cc8-4fc1-a059-3ac850f250a4 · outbound

This paper cites an unresolved cited work.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:16:16.329506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:09.810668Z digest=sha256:c6b3682be1e46f2e0751864b76b1c4b60610934d6bde8cce21d7c48c51820b16

Observation 10787aca-0c7b-401a-b9d0-e4191886da4b · outbound

This paper cites dLoRA: Dyna- mically orchestrating requests and adapters for LoRA/LLM serving,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air dLoRA: Dyna- mically orchestrating requests and adapters for LoRA/LLM serving,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:16.087853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.079639Z digest=sha256:09bf4c5c24b9b5b1b91d55ad20b65ec851005dccc91eb5faa5f092a4bb10b8da

Observation c64a9223-ab61-4981-9150-229e750358a4 · outbound

This paper cites an unresolved cited work.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:10.200000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:10.200000Z digest=sha256:15a914f69f64c3181d921a123284389155b98700a58c85e465c04874429d0f3c

Observation 0ccef382-454c-4f9d-9482-dc4af97353ec · outbound

This paper cites Reinforcement learning from suboptimal demonstrations based on reward relabeling,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Reinforcement learning from suboptimal demonstrations based on reward relabeling,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:15.866094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.290304Z digest=sha256:d0b380f54fa080ce7ced120b6ca2b25b4c514b248b860d3966da1be677e62725

Observation c86283eb-7464-4c69-ab51-dd5217710f17 · outbound

This paper cites Learning continuous control policies by stochastic value gradients,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Learning continuous control policies by stochastic value gradients,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:15.646303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.397736Z digest=sha256:5b1265be52014ed1b25de0185f90156a63cf4fd705a748399d5da1a4af695f8b

Observation 1ca753ec-6d42-48a9-8ef9-038f05930d14 · outbound

This paper cites Latent space po- licies for hierarchical reinforcement learning,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Latent space po- licies for hierarchical reinforcement learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:15.432404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.498001Z digest=sha256:1b36bf327fd224dd33be40fa84a4ee2205d31b79208e66cdd196744a28709bc8

Observation 3e0d9a1c-28b7-4a38-adb4-774c6d4808c0 · outbound

This paper cites Off-Policy Reinforcement Learning with High Dimensional Reward.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Off-Policy Reinforcement Learning with High Dimensional Reward

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:16:11.948001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.590435Z digest=sha256:f7a034449e247a403eb549034fd24182c65fabbfe3dc269a23683347cd184c80

Observation 2914d65a-e0e0-4655-9fdc-b4bd69cc4b73 · outbound

This paper cites What matters in on-policy reinforcement learning? A large-scale empirical study,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air What matters in on-policy reinforcement learning? A large-scale empirical study,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:14.972253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.798676Z digest=sha256:e6ea1ccfc51748426a8768b061b5f396eb3891998d862b934fbc0640dec93b8f

Observation 27c5d98d-65a6-4b24-aca4-45192b67d154 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air High- resolution image synthesis with latent diffusion models,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:14.761134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.860801Z digest=sha256:9a1ba081d76d8b6649d3a2cf7870b731ee493bed539a588bee994526ca315039

Observation 71a66d57-9358-4c95-813a-9f265633c0d7 · outbound

This paper cites Classifier-free diffusion guidance,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Classifier-free diffusion guidance,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:14.449413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:10.935394Z digest=sha256:e414ba84b3dbd6792ecf13ef7fecbdfc30309bb1ca0f84ced0d0bff11a7b7f86

Observation 2fb2957b-f692-4132-b56e-1782b080610d · outbound

This paper cites Recursive deep models for semantic compositionality over a sentiment treebank,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Recursive deep models for semantic compositionality over a sentiment treebank,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:14.035490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:11.052851Z digest=sha256:66d7495bd663a3c92a036e2f2b0dacdfc932a57212057bed53acfb20a8eb1c38

Observation 998a083a-8dee-46ed-a3f3-14a027a86ee1 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air OPT: Open Pre-trained Transformer Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:11.157376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:11.157376Z digest=sha256:ef8be30dfdbcf5d552763e110227c32885b5ec21008001580d03cd2047804909

Observation 1be01dae-5efd-492f-ac21-e1eff49a3a3f · outbound

This paper cites Early stopping and non- parametric regression: an optimal data-dependent stopping rule,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Early stopping and non- parametric regression: an optimal data-dependent stopping rule,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:13.628848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:11.207737Z digest=sha256:255b1bcc03ee3c01009d9d87469cc89fd0b59373e700e3f29c007a1ad4c8f541

Observation b5087b2f-74c8-4a58-ad29-2bc3295a8db9 · outbound

This paper cites Diffusion Policy: Visuomotor policy learning via action diffusion,.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Diffusion Policy: Visuomotor policy learning via action diffusion,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:16:13.363035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:11.333184Z digest=sha256:3d5b6fa6369545bca4469400e6e9513a0eb171819b6a9168261ff390b4d49605

Observation efb4853b-22a2-4ec8-ac89-b5977e8fb840 · outbound

This paper cites Wider and Deeper LLM Networks are Fairer LLM Evaluators.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air Wider and Deeper LLM Networks are Fairer LLM Evaluators

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:11.555301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:11.555301Z digest=sha256:49d66fbce82decf0dcf1f4a3eb00cbbf5c1638906a6cf7058d3e7c6c90e1de6f

Observation f20496eb-8f9a-4e70-a5ec-00d8f7c75af4 · outbound

This paper cites A Survey of Large Language Models.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air A Survey of Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:06.768756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:06.768756Z digest=sha256:a42dc9ed977948a2e5399a4a958f47a60f31ec1b957466af028f14f37c535243

Pith citing papers

Observation c39a2e92-f70d-4cf4-aefe-52c7ac3f7dc2 · inbound

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air cites this paper.

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T17:16:13.002009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:16:05.343599Z digest=sha256:b0d48dff2fe2b15efd5766123a5d11e011f8789c94a9846a34511c6848f0ab7d