Paper Citation Record · LEDGER

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail)

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 2 inbound Pith citation observations for arXiv:2502.09376.

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

pith.paper-citation-record.v1
2502.09376 v3

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:56:28.113429Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T02:14:38.644041Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:16:57.398617Z

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy31
unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e692fd8d-1ba8-49e4-b864-3ed36e885fa7 · outbound

This paper cites write newline.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T21:56:27.899907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f35f5a6-f48e-423f-a14d-9becfefb8db4 · outbound

This paper cites Intrinsic dimensionality explains the effectiveness of language model fine-tuning.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Intrinsic dimensionality explains the effectiveness of language model fine-tuning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.812312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 354e09e1-7b1e-4b23-96e6-2ddfaf24f344 · outbound

This paper cites B it F it: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) B it F it: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.797593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd86df65-7367-445a-9fbe-0ae25ad9de1a · outbound

This paper cites Global optimality of local search for low rank matrix recovery.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Global optimality of local search for low rank matrix recovery

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.782377Z

Source-reported events for the cited work

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Observation cd6d59e4-768d-4e1d-8ef3-3e13a64bbe81 · outbound

This paper cites and Monteiro, R.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Monteiro, R

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.767377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e06c3974-09de-4777-b4ff-e8b1bff34cc0 · outbound

This paper cites P., and Bernardino, A.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) P., and Bernardino, A

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.752771Z

Source-reported events for the cited work

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Observation 3e580b70-3f66-4966-82aa-c68ca4231d37 · outbound

This paper cites and Recht, B.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Recht, B

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.738862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 98c220fe-5550-4078-a9af-aa78bbf0f120 · outbound

This paper cites Gradient dynamics for low-rank fine-tuning beyond kernels.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Gradient dynamics for low-rank fine-tuning beyond kernels

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T21:56:27.937594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0114dca8-2941-4a94-b09b-38435dd18298 · outbound

This paper cites QL o RA : Efficient finetuning of quantized LLM s.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) QL o RA : Efficient finetuning of quantized LLM s

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.724370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7e6d0f35-5b82-448b-aafe-d56d436a9f58 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) An image is worth 16x16 words: Transformers for image recognition at scale

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.709190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c50a52c0-0a2a-49b6-8ca3-f88ec042fcdc · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.694097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cae99a14-a724-42e8-a266-1b6ac3e5f5ec · outbound

This paper cites S., Gupte, A., and Poggio, T.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) S., Gupte, A., and Poggio, T

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.679582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 91e3008a-c7d3-4b87-94dc-9340e658ead4 · outbound

This paper cites Escaping from saddle points --- online stochastic gradient for tensor decomposition.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Escaping from saddle points --- online stochastic gradient for tensor decomposition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.664330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 017794ee-b27e-40d0-80fe-647da8a56313 · outbound

This paper cites No spurious local minima in nonconvex low rank problems: A unified geometric analysis.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) No spurious local minima in nonconvex low rank problems: A unified geometric analysis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.648522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 12ac7549-30c7-4280-8023-943184755ac3 · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.632480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62ab7258-c005-4f8e-8ebc-cd993b190924 · outbound

This paper cites LoRA+ : efficient low rank adaptation of large models.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) LoRA+ : efficient low rank adaptation of large models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.616156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9d39d05b-8049-47b0-bacb-1de7a9f080a9 · outbound

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

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.601034Z

Source-reported events for the cited work

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Observation 30783878-c28c-4028-86a6-674d4354f617 · outbound

This paper cites Low Rank Regularization : A review.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Low Rank Regularization : A review

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.585418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4fab97aa-446b-4d8d-a51d-f0c629f4c786 · outbound

This paper cites D., and Ryu, E.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) D., and Ryu, E

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.570896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 416b7158-9c77-4b75-acdb-502bbb439a5b · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 20

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Source-reported events for the cited work

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Observation 0ff75e8d-3568-4ada-b755-63560221e9ba · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.555961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ada2276f-4090-4e46-9bee-6286ed4e5a13 · outbound

This paper cites Learning multiple layers of features from tiny images.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Learning multiple layers of features from tiny images

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T21:56:28.005302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5de2cea3-9444-4f8c-93e7-2b4bdf7810d5 · outbound

This paper cites D., Simchowitz, M., Jordan, M.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) D., Simchowitz, M., Jordan, M

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.530964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a38e8f7e-12c7-43a7-a56b-2f63d781f076 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) The power of scale for parameter-efficient prompt tuning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.516380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fe869634-a126-4574-b228-e538d3b8d1fd · outbound

This paper cites Measuring the intrinsic dimension of objective landscapes.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Measuring the intrinsic dimension of objective landscapes

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.501808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a885dbf8-3e97-4355-b330-55683f191372 · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.487069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62e0fc89-f368-43b7-9052-d4add531312a · outbound

This paper cites A kernel-based view of language model fine-tuning.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) A kernel-based view of language model fine-tuning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.471798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 01321cd3-d9b4-4f00-872b-47263ca9aadb · outbound

This paper cites Pi SSA : Principal singular values and singular vectors adaptation of large language models.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Pi SSA : Principal singular values and singular vectors adaptation of large language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.456540Z

Source-reported events for the cited work

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Observation 53222814-a074-4fe6-bb97-c9f8ece95353 · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.440247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c86a463b-5ff5-4562-9603-1fd1fc82901a · outbound

This paper cites and Boyd, S.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Boyd, S

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.424465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3375a43c-ca55-4edf-9cc8-502f574c0119 · outbound

This paper cites Non-square matrix sensing without spurious local minima via the B urer-- M onteiro approach.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Non-square matrix sensing without spurious local minima via the B urer-- M onteiro approach

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.408667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8889ed63-315e-44d9-adf7-ad019701345c · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.392727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ac0b48d3-9b3b-4e98-8fd6-b7b68f15536d · outbound

This paper cites D., Ng, A., and Potts, C.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) D., Ng, A., and Potts, C

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.375214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b3e8238e-5eb3-4d94-b243-d2f9cc0d6c99 · outbound

This paper cites and Sato, I.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Sato, I

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.360267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b40947ee-a377-45cb-a724-b6f05e57a5ec · outbound

This paper cites GLUE : A multi-task benchmark and analysis platform for natural language understanding.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) GLUE : A multi-task benchmark and analysis platform for natural language understanding

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.345341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 477deed3-5f96-4764-a0a5-4a4a73a674d5 · outbound

This paper cites M i L o RA : Harnessing minor singular components for parameter-efficient LLM finetuning.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) M i L o RA : Harnessing minor singular components for parameter-efficient LLM finetuning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.329656Z

Source-reported events for the cited work

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Observation f8ca8107-1019-441d-bed4-f323b40f5527 · outbound

This paper cites and Jacot, A.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Jacot, A

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.314361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85f87de4-738a-4589-b1fc-ec1091800e4a · outbound

This paper cites How over-parameterization slows down gradient descent in matrix sensing: The curses of symmetry and initialization.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) How over-parameterization slows down gradient descent in matrix sensing: The curses of symmetry and initialization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.298215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation de271249-a669-44dd-a697-090ff8b481f9 · outbound

This paper cites and Du, S.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Du, S

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.281989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9409d36-1580-4f62-9fe4-d2cde2b899c8 · outbound

This paper cites and Lee, K.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) and Lee, K

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.265706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85bf6b30-e480-4139-9ae0-99e21e6a5400 · outbound

This paper cites Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T21:56:28.094778Z

Source-reported events for the cited work

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Observation 224d6510-8743-4e55-a701-f9e367683784 · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.250106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 697a3dbe-9bbf-4765-b1d1-41004303ff33 · outbound

This paper cites LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T21:56:28.103866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54a33de9-664a-46f0-b306-8939139093f2 · outbound

This paper cites an unresolved cited work.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:56:28.234701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 60523968-22e0-4d39-ab4c-e74ca3149161 · outbound

This paper cites A robustly optimized BERT pre-training approach with post-training.

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail) A robustly optimized BERT pre-training approach with post-training

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:56:28.218464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 4ba7e21e-97fb-462b-a8b5-5eadba40b672 · inbound

Convergent Stochastic Training of Attention and Understanding LoRA cites this paper.

Convergent Stochastic Training of Attention and Understanding LoRA LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail)

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:05:55.048780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c9f8c0a-a952-4bc6-a56e-9d6b44369933 · inbound

High-Dimensional Theory of LoRA Fine-Tuning in a Solvable Attention Model cites this paper.

High-Dimensional Theory of LoRA Fine-Tuning in a Solvable Attention Model LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail)

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:16:57.400233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.