Paper Citation Record · LEDGER

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

As of 12 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 47 inbound Pith citation observations for arXiv:2308.03303.

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

pith.paper-citation-record.v1
2308.03303 v3

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T08:05:33.251722Z

measured 115 of 115 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 47 of 47 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:55:12.200771Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T19:10:05.832087Z

Reference resolution

68 of 68 outbound references displayed

verified exact11
verified fuzzy47
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 442f23a6-d0ab-4d2c-b40d-982dbcc8f0de · outbound

This paper cites write newline.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning write newline

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.230444Z

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Observation 358f292c-2d0b-4243-b7a6-51a1a7154194 · outbound

This paper cites @esa (Ref.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning @esa (Ref

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.220231Z

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Observation 60059079-eb52-47d5-90f2-369a577b972c · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 3

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Observation 7cf47b25-1dc1-4d77-90f7-e23051196be7 · outbound

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LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 4

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Observation 572d5c97-b652-484b-9c16-885c64d2f665 · outbound

This paper cites Falcon-40b: an open large language model with state-of-the-art performance.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Falcon-40b: an open large language model with state-of-the-art performance

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.213111Z

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Observation 49c786c7-f4e5-4bd5-8f99-b5c5608ec20b · outbound

This paper cites Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, and Eric Chu et al.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, and Eric Chu et al

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.226668Z

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Observation 52f2f4c5-f1d1-4fec-8f45-ceae88803e2c · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-24T08:06:03.871751Z

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Observation 45ed7e35-1f4c-4545-81e4-224636cbc880 · outbound

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

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning B it F it: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 8

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.711687Z

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Observation 20e3d23b-06fe-4dfd-84e0-135fb463bb3b · outbound

This paper cites Language models are few-shot learners.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Language models are few-shot learners

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.109913Z

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Observation 4ca78237-8d2f-4aa1-aaaf-b5c783adaa78 · outbound

This paper cites One-for-all: Generalized lora for parameter-efficient fine-tuning.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning One-for-all: Generalized lora for parameter-efficient fine-tuning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.086527Z

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Observation 0cd47c57-7d9c-486d-9d53-d3fc9268b5d9 · outbound

This paper cites Training Deep Nets with Sublinear Memory Cost.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Training Deep Nets with Sublinear Memory Cost

Reference 11

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Observation a020ae7e-a545-4a55-b25b-bbfbeb13026e · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Gonzalez, Ion Stoica, and Eric P

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.120019Z

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Observation 86a16296-e5e0-4732-b759-4fc8f9f517d3 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Scaling Instruction-Finetuned Language Models

Reference 13

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Observation b951a25f-4cf7-42f0-885e-de71ad7cffdc · outbound

This paper cites Unimax: Fairer and more effective language sampling for large-scale multilingual pretraining.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unimax: Fairer and more effective language sampling for large-scale multilingual pretraining

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.188696Z

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Observation 47fe3c8c-d391-4f85-93ac-a7433d5cef1e · outbound

This paper cites Think you have solved question answering? try arc, the ai2 reasoning challenge.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Think you have solved question answering? try arc, the ai2 reasoning challenge

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.180138Z

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Observation 45eca4cc-8b90-454c-98cc-317ccd9792ce · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.177414Z

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Observation a000ebd1-4b44-4bfc-8176-ed8ca9963dc1 · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 17

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Observation 1b122660-5cd2-4515-bca8-7cd995f662f7 · outbound

This paper cites 8-bit optimizers via block-wise quantization.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning 8-bit optimizers via block-wise quantization

Reference 18

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Observation 639896a1-47ff-4c28-bec9-dc8726028eea · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning QLoRA: Efficient Finetuning of Quantized LLMs

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-24T08:06:03.880596Z

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Observation 003c5c9f-723a-4065-a862-02b62558041a · outbound

This paper cites BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 20

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.703452Z

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Observation 6cdea12f-e901-413f-95e9-3ebdbf80dd3c · outbound

This paper cites Open llm leaderboard.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Open llm leaderboard

Reference 21

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Observation 264be4f7-6f64-41c4-9549-4a07da1b2c20 · outbound

This paper cites A framework for few-shot language model evaluation, September 2021.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning A framework for few-shot language model evaluation, September 2021

Reference 22

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.706414Z

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Observation c6cfed2f-40b4-46d7-aa8e-99d3ff568a69 · outbound

This paper cites PPT : Pre-trained prompt tuning for few-shot learning.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning PPT : Pre-trained prompt tuning for few-shot learning

Reference 23

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.701064Z

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Observation b26856ca-ca56-48d9-825f-f4e78c48c25d · outbound

This paper cites Deberta: Decoding-enhanced bert with disentangled attention.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Deberta: Decoding-enhanced bert with disentangled attention

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.154310Z

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Observation 53edb4d7-8638-400b-888d-b163f9595e19 · outbound

This paper cites Measuring massive multitask language understanding.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Measuring massive multitask language understanding

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.145621Z

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Observation c10bb012-c057-4b71-9780-514004942810 · outbound

This paper cites Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 26

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Observation 0e438317-165c-43fb-9563-12d63e4d180f · outbound

This paper cites Parameter-efficient transfer learning for nlp.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Parameter-efficient transfer learning for nlp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.166533Z

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Observation 939c912c-be8b-4d42-97b9-aadd8a91cd77 · outbound

This paper cites Lo RA : Low-rank adaptation of large language models.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Lo RA : Low-rank adaptation of large language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.165326Z

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Observation 062f81f4-ff5c-4f1d-9525-00d4181ac7e6 · outbound

This paper cites Lorahub: Efficient cross-task generalization via dynamic lora composition.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Lorahub: Efficient cross-task generalization via dynamic lora composition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.155524Z

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Observation 103e7785-229d-40c2-8b80-50e7007ad897 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Quantization and training of neural networks for efficient integer-arithmetic-only inference

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.121996Z

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Observation de38019a-ff8f-4e5d-bbd7-150ce4adcc36 · outbound

This paper cites Gonzalez.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Gonzalez

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.127068Z

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Observation 4264a361-e2ff-4a8a-9dd4-e81c14bf387a · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.200730Z

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Observation 7a16d951-64e3-40c0-b019-a67ff313a7b3 · outbound

This paper cites Semantic sentence matching with densely-connected recurrent and co-attentive information.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Semantic sentence matching with densely-connected recurrent and co-attentive information

Reference 33

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.698828Z

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Observation 433e8d73-fb7e-40a6-88bd-a93d6a4626b9 · outbound

This paper cites Reducing activation recomputation in large transformer models.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Reducing activation recomputation in large transformer models

Reference 34

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Observation 85fb1ccc-aea6-41d1-86bb-24396d892beb · outbound

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

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning The power of scale for parameter-efficient prompt tuning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.152856Z

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Observation 2feef5f0-4623-4f51-9866-ad8061ffc5ef · outbound

This paper cites Prefix-tuning: Optimizing continuous prompts for generation.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Prefix-tuning: Optimizing continuous prompts for generation

Reference 36

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Observation b71385c3-589b-433d-bea5-52e826fe6dec · outbound

This paper cites Stack more layers differently: High-rank training through low-rank updates.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Stack more layers differently: High-rank training through low-rank updates

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.169576Z

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Observation 05ebadec-728d-4c4a-9191-47cadbaec473 · outbound

This paper cites Truthfulqa: Measuring how models mimic human falsehoods.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Truthfulqa: Measuring how models mimic human falsehoods

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.157045Z

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Observation a70ba7b4-42b0-44a3-8dd1-4eef4c442f34 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.197978Z

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Observation 5b5a90ae-63d3-42b8-9557-3bb39e62bef2 · outbound

This paper cites Gpt understands, too.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Gpt understands, too

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.181264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1f79757a-5031-4f12-b636-32264ffeba97 · outbound

This paper cites Roberta: A robustly optimized bert pretraining approach.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Roberta: A robustly optimized bert pretraining approach

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.191950Z

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Observation 89287c10-b913-44ae-9cb9-355e1b4850fa · outbound

This paper cites Decoupled weight decay regularization.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Decoupled weight decay regularization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.140645Z

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Observation 39da7f75-5e7f-4ad3-ac6f-6efcd4dc7c09 · outbound

This paper cites Gpt-4 technical report.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Gpt-4 technical report

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.206098Z

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Observation c1368b10-3152-48cd-a3d3-979c70e5b929 · outbound

This paper cites Training language models to follow instructions with human feedback.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Training language models to follow instructions with human feedback

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.137637Z

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Observation 64089540-560c-4f25-be53-aabf13aaa8ac · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 45

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Observation f88f6c02-ec99-4394-b5b8-5de0afd15d0f · outbound

This paper cites Zero: Memory optimizations toward training trillion parameter models.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Zero: Memory optimizations toward training trillion parameter models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.194926Z

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Observation 8e93b333-92f9-4278-85f8-3ca18ccbd760 · outbound

This paper cites Zero-offload: Democratizing billion-scale model training.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Zero-offload: Democratizing billion-scale model training

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.202848Z

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Observation 288152c9-da21-4440-9f5f-761290cb083c · outbound

This paper cites Megatron-lm: Training multi-billion parameter language models using model parallelism.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Megatron-lm: Training multi-billion parameter language models using model parallelism

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.172445Z

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Observation 9c86b226-4fd5-4f2f-87ce-e0fe11e7baaf · outbound

This paper cites Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.059791Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0c3de994-c53c-4dcc-9680-687fb38d3911 · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Manning, Andrew Ng, and Christopher Potts

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.099663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 41d3285f-4a40-4d12-9406-db9eac259952 · outbound

This paper cites Hashimoto.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Hashimoto

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.136603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ac85a8ab-b792-4914-a303-53d135d5b054 · outbound

This paper cites Llama: Open and efficient foundation language models, 2023 a.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Llama: Open and efficient foundation language models, 2023 a

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.099185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1288c17f-6afb-4b7f-80b1-2a544a80e0bc · outbound

This paper cites Llama 2: Open foundation and fine-tuned chat models, 2023 b.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Llama 2: Open foundation and fine-tuned chat models, 2023 b

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.203377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 84e3185b-3778-40cf-ba02-4838f2c19480 · outbound

This paper cites Attention is all you need.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Attention is all you need

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.126786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d401b4b1-4478-4d4a-8257-5118debdc895 · outbound

This paper cites Powersgd: Practical low-rank gradient compression for distributed optimization.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Powersgd: Practical low-rank gradient compression for distributed optimization

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.083079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1d74bad4-1afb-4bf3-81bc-c0aeb27ecc7c · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-05-24T08:06:04.149916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 415b37ec-a5d5-4b8f-ab4d-41d7ff74b838 · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.077866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 34f3bd10-cd6a-4b68-a01b-4ff44187de92 · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-05-24T08:06:04.186011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1804d4a1-fb82-4e64-b269-78b78ab1b8c7 · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-05-24T08:06:04.093034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 82a84a5a-eb6c-4b9b-8a9d-b55f085f1933 · outbound

This paper cites Finetuned language models are zero-shot learners.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Finetuned language models are zero-shot learners

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.187692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 469d0048-a69d-432c-bc91-2c16b128db80 · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-05-24T08:06:04.184347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e0da3654-6adc-4144-893a-8693eeda1daf · outbound

This paper cites m T 5: A massively multilingual pre-trained text-to-text transformer.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning m T 5: A massively multilingual pre-trained text-to-text transformer

Reference 62

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.709304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1f231075-f618-41d2-b4db-36d6d22b3884 · outbound

This paper cites ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models

Reference 63

Resolution: verified exact; doi, observed 2026-05-24T08:06:03.696222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 649611cd-7a2f-48d3-a373-8e2633c3139e · outbound

This paper cites Hellaswag: Can a machine really finish your sentence?.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Hellaswag: Can a machine really finish your sentence?

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.088787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6df7512b-fef0-4e41-8e16-9757165ca005 · outbound

This paper cites Evaluation and optimization of gradient compression for distributed deep learning.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Evaluation and optimization of gradient compression for distributed deep learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.169870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d562ddec-c324-4a5b-9d17-fba6a41466e1 · outbound

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

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Adaptive budget allocation for parameter-efficient fine-tuning

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.158387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ee0010ba-1927-4b27-852d-5da38f47acf3 · outbound

This paper cites Pytorch fsdp: Experiences on scaling fully sharded data parallel.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Pytorch fsdp: Experiences on scaling fully sharded data parallel

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T08:06:04.191642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ca963b53-725b-4cb2-8b79-8b25cbcec6bf · outbound

This paper cites an unresolved cited work.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-05-24T08:06:04.199196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation f521ea77-83c2-48b8-9a45-46a795f2ff7e · inbound

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection cites this paper.

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:51:50.289941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 93f9cac5-41b7-462f-982d-65b80acaf1f2 · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 135

Resolution: verified exact; local_arxiv, observed 2026-05-13T11:32:37.178423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b0853ef-8030-41db-8f0c-af7a20ee9c2e · inbound

S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity cites this paper.

S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:12.200771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cdab6a2-10f5-4154-b204-6b905bddb292 · inbound

FineGates: LLMs Finetuning with Compression using Stochastic Gates cites this paper.

FineGates: LLMs Finetuning with Compression using Stochastic Gates LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.104166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17fef881-e036-41be-82e7-83a9fe7e10c2 · inbound

VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition cites this paper.

VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T23:42:24.264635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f090a718-778b-461d-b209-45b1fc8c6f7a · inbound

Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring cites this paper.

Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.334979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f93ced4-668b-445d-be71-f5ac8c0f261a · inbound

GWT: Scalable Optimizer State Compression for Large Language Model Training cites this paper.

GWT: Scalable Optimizer State Compression for Large Language Model Training LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-05-23T05:57:36.661753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ff930418-18d6-4fb7-9ccc-6b2f49bd7a61 · inbound

SEAL: Entangled White-box Watermarks on Low-Rank Adaptation cites this paper.

SEAL: Entangled White-box Watermarks on Low-Rank Adaptation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:25.230824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 563cc2d6-bbed-48de-888f-94e29d3af971 · inbound

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning cites this paper.

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-10T20:26:11.243027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fc55bd4-7136-4912-a961-96153773d3e0 · inbound

Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.

Parameter-Efficient Fine-Tuning for Foundation Models LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 107

Resolution: unresolved; no resolver link, observed 2026-08-10T15:38:03.179096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f63ec6af-3d41-4fc2-acda-9c46899a1baf · inbound

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning cites this paper.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T11:16:55.848370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1a0b597-b711-43eb-8665-10a9fb8ca343 · inbound

Memory-Efficient Fine-Tuning of Transformers via Token Selection cites this paper.

Memory-Efficient Fine-Tuning of Transformers via Token Selection LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.499818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d78bc88d-8e1a-4fcd-a8da-02a88cfa8749 · inbound

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs cites this paper.

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-22T01:20:52.118075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 49414622-fb2a-4468-919f-2ecbc9b10f6c · inbound

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models cites this paper.

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:42:47.242333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96b3f61c-4fb1-4f8d-9233-9d71a06b255c · inbound

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting cites this paper.

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:58.292460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f6c7e3b-f613-4e7b-aa57-f37df9495d79 · inbound

FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts cites this paper.

FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T12:09:15.974806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1104e002-17bf-48f4-8cf3-3e7905f4bbe2 · inbound

MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation cites this paper.

MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-19T10:52:15.099126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c57aa437-3d80-4c92-a19d-af80e240946c · inbound

Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation cites this paper.

Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:18:25.577452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73226ca3-5aff-4b80-840d-df22a66609df · inbound

Dynamic Sparse Training of Diagonally Sparse Networks cites this paper.

Dynamic Sparse Training of Diagonally Sparse Networks LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T04:15:17.585257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a31cc8e6-f2e0-45ba-8641-ba4a9f8e9296 · inbound

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence cites this paper.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 112

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:55.915303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86159505-56da-466d-b389-dda41e029302 · inbound

Improving LoRA with Variational Learning cites this paper.

Improving LoRA with Variational Learning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:29.312251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6837c7-1911-4314-905f-1ef8bbbf7e3a · inbound

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models cites this paper.

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:12.331356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c77f119-3df5-4ca2-88b5-d56227742f61 · inbound

LogTinyLLM: Tiny Large Language Models Based Contextual Log Anomaly Detection cites this paper.

LogTinyLLM: Tiny Large Language Models Based Contextual Log Anomaly Detection LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:20:42.301515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73a82e9a-bf96-4f26-b2c0-8f502bab158e · inbound

GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation cites this paper.

GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T17:33:16.928324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15a616a7-8ec7-4a1c-aca6-a600fc46f61e · inbound

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis cites this paper.

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-18T03:02:22.018781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 35b39784-16d7-4b74-b2eb-3271b3df96d6 · inbound

NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion cites this paper.

NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-25T08:00:29.669192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8dfc3724-26c7-4709-910e-631d36d1b756 · inbound

CrossEarth-Gate: Fisher-Guided Adaptive Tuning Engine for Efficient Adaptation of Cross-Domain Remote Sensing Semantic Segmentation cites this paper.

CrossEarth-Gate: Fisher-Guided Adaptive Tuning Engine for Efficient Adaptation of Cross-Domain Remote Sensing Semantic Segmentation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-03T20:20:35.847031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c7d63e2-e9a6-41a4-8dac-b02c75dcd1fe · inbound

FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On cites this paper.

FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T06:10:58.946249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1b28dcc7-149e-4566-8590-0c65fcacd896 · inbound

Crowded in B-Space: Calibrating Shared Directions for LoRA Merging cites this paper.

Crowded in B-Space: Calibrating Shared Directions for LoRA Merging LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-10T07:52:14.020077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b8f23920-a24a-4004-b011-f34e6d03f989 · inbound

TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.

TLoRA: Task-aware Low Rank Adaptation of Large Language Models LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T09:48:48.151092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 552578cf-06ff-4bc1-b346-0d38db437de0 · inbound

DP-FlogTinyLLM: Differentially private federated log anomaly detection using Tiny LLMs cites this paper.

DP-FlogTinyLLM: Differentially private federated log anomaly detection using Tiny LLMs LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T02:53:29.815446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0e183019-9b92-4903-bf8c-387eeb47bcd1 · inbound

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity cites this paper.

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-11T19:01:17.868182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ccde1026-bc00-4991-88c8-e11a7f4816dc · inbound

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training cites this paper.

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 205

Resolution: verified exact; local_arxiv, observed 2026-05-11T04:05:56.672805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d10301c7-b707-4ba1-bbc0-008be6f55349 · inbound

S2FT: Parameter-Efficient Fine-Tuning in Sparse Spectrum Domain cites this paper.

S2FT: Parameter-Efficient Fine-Tuning in Sparse Spectrum Domain LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-05-12T08:31:25.620627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a5f2bf24-d43a-449c-be6a-9307452c5147 · inbound

HELLoRA: Hot Experts Layer-Level Low-Rank Adaptation for Mixture-of-Experts Models cites this paper.

HELLoRA: Hot Experts Layer-Level Low-Rank Adaptation for Mixture-of-Experts Models LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-20T23:29:12.682709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cd70d297-c054-4ca4-8849-2c017704d3e5 · inbound

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data cites this paper.

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-07-02T01:56:28.096334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5b54bc41-8cba-4070-89bf-9e90f5f5ef78 · inbound

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation cites this paper.

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 85

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T23:07:27.005466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d58a409b-8565-4ebe-bb71-0134865a0b72 · inbound

The Hidden Power of Scaling Factor in LoRA Optimization cites this paper.

The Hidden Power of Scaling Factor in LoRA Optimization LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 74

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T14:08:21.886190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7f614484-6c83-42ac-b4ad-a670d18a609f · inbound

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices cites this paper.

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-04T00:39:16.823803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation defdf4e7-d3f4-49ba-b0e0-ca44150a045b · inbound

EPTS: Elastic Post-Training Sparsity for Efficient Large Language Model Compression cites this paper.

EPTS: Elastic Post-Training Sparsity for Efficient Large Language Model Compression LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-07-04T19:10:05.834097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 771d6e7a-818a-4f19-b56d-a54699744e9f · inbound

BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning cites this paper.

BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-06-30T08:04:28.526837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6bdfe00a-0218-4701-a7d5-c8f6269c0520 · inbound

AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance cites this paper.

AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-06-30T08:04:28.836451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cc95c155-6589-4428-96f8-331a15f479da · inbound

Probing Memorization of Tabular In-Context Learning cites this paper.

Probing Memorization of Tabular In-Context Learning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T09:25:40.747132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c692bccc-4448-4a9d-b0d3-3062d758ed51 · inbound

RSRA: Training-Free Probing of Representation Sensitivity for Efficient LoRA Rank Allocation cites this paper.

RSRA: Training-Free Probing of Representation Sensitivity for Efficient LoRA Rank Allocation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T16:23:01.601553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bf00fb3-5a5b-494b-bb28-606af656d52d · inbound

RSRA: Training-Free Probing of Representation Sensitivity for Efficient LoRA Rank Allocation cites this paper.

RSRA: Training-Free Probing of Representation Sensitivity for Efficient LoRA Rank Allocation LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T04:34:34.499526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c69e299f-8a47-4127-bd18-e32f58305c61 · inbound

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers cites this paper.

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T18:39:20.155492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93916948-413b-4e24-8539-f4cfe80c125d · inbound

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers cites this paper.

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T04:12:47.933215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.