Paper Citation Record · LEDGER

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2502.10239.

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

pith.paper-citation-record.v1
2502.10239 v3

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:56:25.791922Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

30 of 30 outbound references displayed

verified exact3
verified fuzzy14
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a804e73d-6fa0-4549-8585-3b433f8d1a8c · outbound

This paper cites write newline.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.697842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4afa8e17-0b37-47df-bcfc-14f804bdaeb5 · outbound

This paper cites Fedrolex: Model-heterogeneous federated learning with rolling sub-model extraction.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Fedrolex: Model-heterogeneous federated learning with rolling sub-model extraction

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.273343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation baaaafbe-3cb9-4fa8-b0bd-5557c35acf55 · outbound

This paper cites SL o RA : Federated parameter efficient fine-tuning of language models.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices SL o RA : Federated parameter efficient fine-tuning of language models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.265334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ca7f3293-642e-43ab-915e-7c7db1915219 · outbound

This paper cites Gradients without Backpropagation.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Gradients without Backpropagation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.709239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3c154d4-5c78-44e0-a9c5-9e1b15da5ec2 · outbound

This paper cites R., Angeli, G., Potts, C., and Manning, C.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices R., Angeli, G., Potts, C., and Manning, C

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.712904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b111fcc0-357b-497e-ab65-1fab460ac67b · outbound

This paper cites A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.256666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 99c0d48f-f243-4c4c-8cd9-24a0b41acb8f · outbound

This paper cites Expanding the Reach of Federated Learning by Reducing Client Resource Requirements.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.719468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 112bf96f-f486-404d-99bd-479b88f844c8 · outbound

This paper cites B ool Q : Exploring the surprising difficulty of natural yes/no questions.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices B ool Q : Exploring the surprising difficulty of natural yes/no questions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.723112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99ba409e-2fa9-40fb-8625-d2138e26cbf5 · outbound

This paper cites N., and Zhou, Y.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices N., and Zhou, Y

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.248034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 83ae8fe5-4fdb-490a-ba51-17ec8c88d8c1 · outbound

This paper cites BAFFLE: A Baseline of Backpropagation-Free Federated Learning.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices BAFFLE: A Baseline of Backpropagation-Free Federated Learning

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T18:56:26.086301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae4e5af4-3bae-48d6-8401-5fd62c6a89fd · outbound

This paper cites Making pre-trained language models better few-shot learners.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Making pre-trained language models better few-shot learners

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.239619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ae281c4-0daf-4fd3-b02b-6b1b3b661666 · outbound

This paper cites J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.230551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e76563ae-c4b3-41fc-996c-eef5fdc14266 · outbound

This paper cites an unresolved cited work.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.736092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec52d13b-8c53-41d3-909a-9585e84126d7 · outbound

This paper cites Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.738618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0573a939-d2d1-484c-8668-af2af531dc9c · outbound

This paper cites On the convergence of zeroth-order federated tuning for large language models.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices On the convergence of zeroth-order federated tuning for large language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.221401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 542c8775-7e0d-4e58-8b0c-95110b477550 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.744241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22b1d21e-5e63-4a02-871c-eb11e623aa0a · outbound

This paper cites D., Chen, D., and Arora, S.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices D., Chen, D., and Arora, S

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.212047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f607d714-8a9d-40a5-8185-73e49022648f · outbound

This paper cites an unresolved cited work.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.751311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d515c248-a362-4a4e-8fee-20e8b908e014 · outbound

This paper cites Black-box generalization: Stability of zeroth-order learning.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Black-box generalization: Stability of zeroth-order learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.197495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7dd17cb2-150d-4f3d-bc22-38a21740f023 · outbound

This paper cites Thinking Forward: Memory-Efficient Federated Finetuning of Language Models.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Thinking Forward: Memory-Efficient Federated Finetuning of Language Models

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T18:56:25.923898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6e039505-fcb6-47d0-a741-07a2fa020ae5 · outbound

This paper cites Aggregating capacity in fl through successive layer training for computationally-constrained devices.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Aggregating capacity in fl through successive layer training for computationally-constrained devices

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.187931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3433cf1c-7853-436b-830e-2d7fa4cee584 · outbound

This paper cites Federated learning for computationally constrained heterogeneous devices: A survey.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Federated learning for computationally constrained heterogeneous devices: A survey

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.178270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 19f6ef8b-e32f-496f-96e2-629da07d62bc · outbound

This paper cites an unresolved cited work.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.768674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aafa219e-5b2c-492d-bd21-36e4b66055bb · outbound

This paper cites Federated full-parameter tuning of billion-sized language models with communication cost under 18 kilobytes.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Federated full-parameter tuning of billion-sized language models with communication cost under 18 kilobytes

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.167833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 638aad1e-bdd0-4ef6-afca-80fca62c70cb · outbound

This paper cites an unresolved cited work.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T18:56:26.156503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 567397c8-6538-4c19-90d5-9e3f9b55a08a · outbound

This paper cites D., Ng, A.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices D., Ng, A

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.778192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3079c42e-094a-4f4a-a9a8-ef00d831b47a · outbound

This paper cites an unresolved cited work.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T18:56:26.138569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 72a4e809-3c9b-4feb-9910-74cef78935f9 · outbound

This paper cites Compressing RNNs for IoT devices by 15-38x using Kronecker Products.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Compressing RNNs for IoT devices by 15-38x using Kronecker Products

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T18:56:25.909284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f2019943-4e9b-4a09-9902-960778133100 · outbound

This paper cites Progfed: effective, communication, and computation efficient federated learning by progressive training.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Progfed: effective, communication, and computation efficient federated learning by progressive training

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.127830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9a8765f3-f07f-454d-8c6e-896dd2650a09 · outbound

This paper cites FwdLLM : Efficient federated finetuning of large language models with perturbed inferences.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices FwdLLM : Efficient federated finetuning of large language models with perturbed inferences

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T18:56:26.117193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.