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Paper Citation Record · LEDGER

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation

As of 19 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2505.23094.

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

pith.paper-citation-record.v1
2505.23094 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:56:53.491420Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

68 of 68 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved65
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ca0b6fc-f0ec-49aa-8481-806934849642 · outbound

This paper cites online" 'onlinestring :=.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation online" 'onlinestring :=

Reference 1

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source=arxiv_source observed=2026-08-07T12:56:48.956836Z digest=sha256:5e1bfe703055ef133f899272cec3a31dd6c7c9f9384a4e9fe03eac0227c04a27

Observation 772970f9-25e5-4619-9cfa-96585a0affe7 · outbound

This paper cites write newline.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation write newline

Reference 2

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source=arxiv_source observed=2026-08-07T12:56:48.983276Z digest=sha256:0df80390255dd01463a6beb3029ef254ffb2cf92ed1c5b700b63e2f4d75acdd1

Observation 614b927c-bac2-480d-bd63-147f6848bdab · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 3

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source=arxiv_source observed=2026-08-07T12:56:49.026580Z digest=sha256:41e65d4b2fe57c9b6d51f17b9737c4d5bad3e86dff14495b5106624a2c70698d

Observation 6c535ddd-c6f2-4672-86e3-5b0316a747d5 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 4

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Observation 9f4bf275-5eac-4eda-a839-1b8129803259 · outbound

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

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 5

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source=arxiv_source observed=2026-08-07T12:56:49.252167Z digest=sha256:c413d62472266f07e3cd1bef944240217f42a4ed13e45349a41c079064428f7a

Observation 1a642b20-7f07-4439-93bd-9b16e2e25b63 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 6

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source=arxiv_source observed=2026-08-07T12:56:49.354285Z digest=sha256:dfa04bdf2581dfe927e23c889364ddc904dfce63eb612b45eb9f420ac0b072e6

Observation 4db68be5-b7f3-4bb2-96dd-453ff70c0b2b · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 7

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Observation 8eadd083-5ef3-4797-a11f-54273758ea4d · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-07T12:56:49.474471Z digest=sha256:1463297a934142c9c50146372414781b9bfe9dd85c2b20e70c814433979fe404

Observation 7e207fe9-bdb0-43e6-8ffd-f487645014a4 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-07T12:56:49.522228Z digest=sha256:78c7e851fa39af0b8861ec81fb882e78609c86080874241d7ffab4639407fbce

Observation 1987957f-6eb5-4953-87cb-d6b91aac1091 · outbound

This paper cites SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

Reference 10

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source=arxiv_source observed=2026-08-07T12:56:49.599886Z digest=sha256:34fa81b10adc57708c85c1db701b20697791d03d2ae5688637c37dbd5453512a

Observation feb3ab40-3542-4bc5-abbc-b12f6eff2eab · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 17016420-7995-4654-8f92-57afb46e764d · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 12

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Observation 1eb47673-376e-42f4-bc42-c572c518928d · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 13

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Observation 9659ae7c-bbe5-4087-9139-acbf0559f55e · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 14

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source=arxiv_source observed=2026-08-07T12:56:49.899698Z digest=sha256:09c4e8ac80ff0db8b52c42648dba6168b96c7fbd9877457d65bc2ca3ba1521fc

Observation 98e94dde-014e-48e4-a371-ce294e712a30 · outbound

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

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 15

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Observation 1c1326f5-5fa3-4adf-a857-810abf5f5f2b · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:49.972481Z digest=sha256:43f245d756047e35a5e611f6294bfe1c527f6d8d1f4dfbad14eadd3ae1d673d6

Observation ead4524a-68f9-438b-bebc-40a840d72ac4 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 17

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Observation dfe9c070-53a7-4071-a6da-a0e05cf0d086 · outbound

This paper cites TriLoRA: Integrating SVD for Advanced Style Personalization in Text-to-Image Generation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation TriLoRA: Integrating SVD for Advanced Style Personalization in Text-to-Image Generation

Reference 18

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verified exact
local_arxiv, observed 2026-08-07T12:56:54.129162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0d42d794-501a-4cd7-90a6-557c51663075 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 19

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raw_fallback, observed 2026-08-07T12:56:55.327029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 90e4b258-f9ab-4db2-9f5f-48f8cba04033 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 20

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Observation 60f2895d-e6e4-403e-aac4-09edf17a3ef5 · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 21

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Observation 47f0c38a-ad61-4ce8-8206-d8ba346f9348 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:50.260648Z digest=sha256:e5a943e15ff81fc24354ba227df4a9e122905d8f92865d645e44d1931c69f1a5

Observation eb1c6da4-568f-4f59-ada0-c9354b2e8999 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 23

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source=arxiv_source observed=2026-08-07T12:56:50.347455Z digest=sha256:8bc94f63e2ddce2a59aa5e160ef6d159980125c53a9a06c22d3aa618643dfbba

Observation 038993e7-6df5-478d-8bfd-b28463de1aa5 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 24

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source=arxiv_source observed=2026-08-07T12:56:50.392573Z digest=sha256:4b4ec582c16f340f412a0a43f0fd42ee8f745ed91d21eaff743243848820c2b9

Observation 4c753790-2f88-457f-834c-f87194925986 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation LoRA: Low-Rank Adaptation of Large Language Models

Reference 25

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source=arxiv_source observed=2026-08-07T12:56:50.428389Z digest=sha256:06a79edf1ec67c80f9093506018a0c4bc161100002f3ab4745106b62d268babe

Observation 406df8a0-638b-4d79-a790-89c9bd2bfca1 · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 26

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source=arxiv_source observed=2026-08-07T12:56:50.473580Z digest=sha256:8c0cdc2ed7c1d3e26a1d3a30518d9b369fca34ae469ea6ca14590bae59f47c2d

Observation 3250105b-6543-4f89-aeca-7a5a8124601c · outbound

This paper cites FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.559783Z digest=sha256:ea7d02d511f76d460b9f5f05cc07a2ada6688c6a195e01db1a5c48ae1540645b

Observation 6c2f0713-e5c6-41f6-bb79-48227136aba3 · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation VeRA: Vector-based Random Matrix Adaptation

Reference 28

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no resolver link, observed 2026-08-07T12:56:50.611625Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.611625Z digest=sha256:1912946dd816ef940bc44a63a77138ae97ab460bb52bcd99d5cfff8eeb2228e4

Observation 1bc11847-01dd-493b-9c6d-5f29cf5762d9 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 29

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no resolver link, observed 2026-08-07T12:56:50.650257Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.650257Z digest=sha256:9f5e7c6b68de31308ea9eb355cb577dffefc7380254be7ad3ba9491ac089d7bf

Observation 08ff6a5f-b83f-4e92-aaf3-b4a0781dddb9 · outbound

This paper cites Measuring the Intrinsic Dimension of Objective Landscapes.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Measuring the Intrinsic Dimension of Objective Landscapes

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.695663Z digest=sha256:4556b82e58869f6d858bbe3ca483bf5131774b729027ae410198931f983d386f

Observation 85bd7e26-3591-4d20-84a9-159d907207a0 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.732444Z digest=sha256:d08050f7d3877a39fd7d84ea6879459ad3af725af8ed9e053920c0303b30d550

Observation c134938e-d312-4aa1-b2ad-1a813e0bd2c3 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.798645Z digest=sha256:045f9be858c519981db080b03209f3d7d7669978a84bd6bb992c2c33b8d096eb

Observation 60955e72-c881-47c6-a171-eb9863c74cf6 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 33

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no resolver link, observed 2026-08-07T12:56:50.874745Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.874745Z digest=sha256:a230c0232f5d548eed13b1f7f27af757304f65c4e3abf84336d48b9bc3d9eaaa

Observation 92c7d13e-ba6b-4f59-887c-f867d163ffa3 · outbound

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

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 34

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no resolver link, observed 2026-08-07T12:56:50.911687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:50.911687Z digest=sha256:51b46d8f0c7d231d1c59998eb02eed5293b6f5fda3bf8677f8edf112f9f7b104

Observation 3e43ce8a-f62a-4134-a9d2-eb8ca11c12a0 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 35

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source=arxiv_source observed=2026-08-07T12:56:50.955582Z digest=sha256:b1050b414984748e1226d16b39847d030b6414221def9520dc7fd21b1db51ee9

Observation 3bd94438-8996-4db4-a437-e165a9d2b8e1 · outbound

This paper cites PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 36

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no resolver link, observed 2026-08-07T12:56:51.044274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.044274Z digest=sha256:14ff53ad8935695bd14de6483c1e42a91c8404b301fcf6a3f1fe8e1cf86b500e

Observation ab64a806-c0ba-4b3e-97bf-0c18372255ef · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 37

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T12:56:51.113652Z digest=sha256:f8e6ecc62c15d4050ace6769a29981290d67dbad304a917b7d62f7ec14d8a8f4

Observation 3b12dfd5-e290-4470-871a-65e9a6f516c4 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 38

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no resolver link, observed 2026-08-07T12:56:51.142665Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.142665Z digest=sha256:71ca6efd0db4833ebf5406d5c036df5ca96c5385968048007d80a4f6c02fa98d

Observation 0f41ec39-c53f-4df4-bad1-eabcc13f0278 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.198620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.198620Z digest=sha256:cf1087431ed6974bec0f991012bd50e26bc3b038c5d45658bb5e6f5328e0224c

Observation 066a85f9-69f5-4d63-9387-44265fd4bb41 · outbound

This paper cites AdapterFusion: Non-Destructive Task Composition for Transfer Learning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation AdapterFusion: Non-Destructive Task Composition for Transfer Learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.280885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.280885Z digest=sha256:f6ef3251120780fd86586d0d9a8b14237dcf1262872aad01b6e15dcfb5547801

Observation 412d7d24-3de1-479b-8195-8f1b11c8383c · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.322054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.322054Z digest=sha256:c4132b3b709b9a832a2301d7101e3e66654724b92abab43aa09f132962dbbbb1

Observation 38f231e8-e570-42a3-a9d9-01605eca9236 · outbound

This paper cites BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:56:53.910034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:51.385076Z digest=sha256:525c9409f6530510e156d8f39bc108ea439cd21de4eb78eaf3000329a39688f6

Observation c3da1922-b8a8-405a-b652-aac7a30f0c21 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:55.065393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:51.460764Z digest=sha256:42f0c069b129d0679c97a2e8a0b51e8df5b4b363a486a7d74400e85cd9b28120

Observation b6dbbc48-a78c-49f7-80c0-332cf8f4ff0a · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.517749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.517749Z digest=sha256:2997a17e2788d5364f207b9da3f679862c6aee2c900049481e313ef94fdee1c4

Observation 8645d99c-6688-4ee2-a047-bc55b370aef4 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.597734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.597734Z digest=sha256:d11474900529c2f41d70cc5b2d5778d505aef6fec3b19d6734847ae899935487

Observation dcf33d18-a400-4702-ba0a-41f7c37537b3 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.672461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.672461Z digest=sha256:4e6cab5a6d667eaf686508e1743d62c06ee89d8500de5ee9176627ef42766604

Observation 7ba04f40-4f82-4ad7-b5a2-2cbf35b6b88e · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.759936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.759936Z digest=sha256:05f053084d55a1a6c5042d017c761242d7400f3b62408c4badb90cca02515664

Observation 9dbb478c-0298-4279-9995-ddbb71eb3d8a · outbound

This paper cites Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.841376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.841376Z digest=sha256:1e2adeb7b843243a6a0e3570b7ece30894815f1b9e498120ae2d24ae7860762a

Observation 8a124e8f-8759-40a2-849e-88028d60b2cb · outbound

This paper cites Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:51.925097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:51.925097Z digest=sha256:588954a2fcb13e718699e7edfd4383f24972a17a8a407758b67db840db8fa354

Observation d53014e1-eb9e-461b-9347-860866c9d17d · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:54.951779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:52.000455Z digest=sha256:caeaa0c0dd79c69f003012920b0bc5ade6e6f4b72684e4b045991e6208f5dad9

Observation 23423fc4-8c29-4922-8637-863edc35a8f6 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.101317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.101317Z digest=sha256:0f74cc67b6a71c839d9d644a0ac6d0fb89309e58c0977d272f48a0551aa2a880

Observation c8775977-fb64-4597-b76d-677539022e15 · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation SocialIQA: Commonsense Reasoning about Social Interactions

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.189707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.189707Z digest=sha256:63e070400d5ee022a268b750e24b5019b1e14d96d617a8b6b7203d9fab0d4145

Observation 1cbf1839-e5a5-4cb9-955f-1f4dce8309c3 · outbound

This paper cites DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.249882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.249882Z digest=sha256:a0f37e8e91754b310b83d8f0dc5b98ae1b984017c6971e354e44738c1b3c1872

Observation 9d73af99-a228-4b6e-872f-c5adb2b7e2a1 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:54.779882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:52.348997Z digest=sha256:7c056e36d0d205ae0e0160d16bdb20ecf954cab29fc984c9b3fed320da728d85

Observation 42cfacb5-e244-4047-ab73-78df1388b5e1 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:54.611917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:52.434103Z digest=sha256:282b974015066e92b13e9bf983fb7231002c4b58703b03dcb4a800cf0b7ee772

Observation 1d230afc-c454-4b01-a4af-5cc7613755dc · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.509554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.509554Z digest=sha256:f9ff240137b7d9e023745b00157b6b53010ff529e618c1fd868cd1c013825e7e

Observation a6e4204e-565c-463d-9f71-05b8dfcc3064 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation LLaMA: Open and Efficient Foundation Language Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.589167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.589167Z digest=sha256:20f30a909e93269f38710e0b1e9a99c369ec1f524fb28611523fa0907c2f8c30

Observation 8c8a6283-fccb-4fa9-b195-cc647ef2e1bb · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.677424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.677424Z digest=sha256:ee8ec8eb25739f2d34e5ac87220be1774ec8af68f787c40ea20bc8a945a0075a

Observation 591586fa-f677-4a93-a88b-84a5c13b1e2e · outbound

This paper cites MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.746767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.746767Z digest=sha256:346d8aac6dac37a2af38d58e529dd9e9b20b7f42523ba19e0d002ca879c2d43d

Observation ca19bc3b-5444-47f1-b1e6-b143cd5084b1 · outbound

This paper cites BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:56:53.658863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:52.831668Z digest=sha256:f9d9f68c6dac8ffeb8d7b821056257a57e28f504b12f67c085fa2e9e06bb811f

Observation 312527e4-cef5-4b02-bd61-8b4ebf6c2730 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.901271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.901271Z digest=sha256:bb3ab2b73530b1efa25aa6d10d8618535d130226101ad69197b414694e08384a

Observation 7d5e6af9-169d-47c5-86ae-4979a1c678c8 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:52.983945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:52.983945Z digest=sha256:2e67013e781c60469bd95216dc2a606a914736c803a0a9169793ee242f4823e6

Observation 4b088509-c8a0-4c50-91b3-2fc77116cfd3 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:53.049016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:53.049016Z digest=sha256:2fb56aef6f2eda5043b63ec093e195e5c91a69273ad90e9108565164732ef2fb

Observation 23f48dfd-b751-4153-915b-f05cf7d24463 · outbound

This paper cites Mixture-of-Subspaces in Low-Rank Adaptation.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Mixture-of-Subspaces in Low-Rank Adaptation

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:53.154441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:53.154441Z digest=sha256:3f8b4adb79cff8796417de3bcae229e96990a83d48e5bf7175aa1c713a67c913

Observation 492ccd47-4c2e-416e-b426-b5b1d3e79990 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:54.471730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:53.243238Z digest=sha256:93152179112721d643250c276445b487debddd58a37a07cadfc25b3a650afd88

Observation d4a9b2c2-83c4-4e50-8ab4-bac69f165638 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:53.335957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:53.335957Z digest=sha256:fcb9af769b2880399dbd615e8450f9d988173e071dceb1dca3fab184e2c9a2ab

Observation 5f3ee00a-b4cd-4497-87bc-f7b973b9915c · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:53.391418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:53.391418Z digest=sha256:90fabeaf835bea8bc16527d4220aca751957fe7fc1feb0f9f169f34c0db46e62

Observation 83e44434-17ee-4b8a-82a8-b40c5f592214 · outbound

This paper cites an unresolved cited work.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation Unresolved cited work

Reference 68

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:56:54.306642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T12:56:53.491420Z digest=sha256:628d82c5d2d4cbf6044616900cd575461aba7732f62be514cb59d52779fad030

Pith citing papers

No inbound Pith citation observations are available.