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Paper Citation Record · LEDGER

Block Circulant Adapter for Large Language Models

As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2505.00582.

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

pith.paper-citation-record.v1
2505.00582 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:45:19.739427Z

measured 42 of 42 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T21:12:04.774915Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T21:13:44.702938Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d3cf664-fc61-4dcf-bbc7-37365fab1d6b · outbound

This paper cites Lamda: Large model fine-tuning via spectrally decomposed low-dimensional adaptation,.

Block Circulant Adapter for Large Language Models Lamda: Large model fine-tuning via spectrally decomposed low-dimensional adaptation,

Reference 1

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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 044177d0-3039-4cfd-8e66-04d1ba997873 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Block Circulant Adapter for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 39454c9f-9a0f-450c-baf3-c95543cc618e · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understand- ing.

Block Circulant Adapter for Large Language Models BERT: pre-training of deep bidirectional transformers for language understand- ing

Reference 11

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raw_fallback, observed 2026-08-16T04:45:20.037882Z

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 c4bebd9b-6c06-4a76-b8cf-755ebb0f7c8a · outbound

This paper cites Automatically constructing a corpus of sentential para- phrases.

Block Circulant Adapter for Large Language Models Automatically constructing a corpus of sentential para- phrases

Reference 13

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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 77556f29-0ebe-4696-a788-74f9d3fc319a · outbound

This paper cites Parameter-efficient fine-tuning with discrete fourier trans- form.

Block Circulant Adapter for Large Language Models Parameter-efficient fine-tuning with discrete fourier trans- form

Reference 14

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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 c9b16887-d9a4-4dea-bee7-907cc13ca6bc · outbound

This paper cites an unresolved cited work.

Block Circulant Adapter for Large Language Models Unresolved cited work

Reference 15

Resolution
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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 80b8587c-f5cb-4f94-b096-49e1014f4089 · outbound

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

Block Circulant Adapter for Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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no resolver link, observed 2026-08-16T04:45:19.664158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.664158Z digest=sha256:24954efa18d8c127042bc2a0d15555b1c61ec4b0991c66012747fc794745b7e4

Observation e532e0df-cecc-4ea0-81d9-02e98607ff97 · outbound

This paper cites Kopiczko, Tijmen Blankevoort, and Yuki M.

Block Circulant Adapter for Large Language Models Kopiczko, Tijmen Blankevoort, and Yuki M

Reference 18

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raw_fallback, observed 2026-08-16T04:45:19.987044Z

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 21157ccf-e949-4d27-9be5-e3326c241f4c · outbound

This paper cites A theoretical framework for back- propagation.

Block Circulant Adapter for Large Language Models A theoretical framework for back- propagation

Reference 19

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raw_fallback, observed 2026-08-16T04:45:19.977831Z

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 43838fca-5a45-4f4e-8b19-41f78cc6b27f · outbound

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

Block Circulant Adapter for Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 21

Resolution
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no resolver link, observed 2026-08-16T04:45:19.676694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 020a4ed4-ad3a-4eb4-9fea-2644b15526cc · outbound

This paper cites Fantastically or- dered prompts and where to find them: Overcoming few- shot prompt order sensitivity.

Block Circulant Adapter for Large Language Models Fantastically or- dered prompts and where to find them: Overcoming few- shot prompt order sensitivity

Reference 22

Resolution
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raw_fallback, observed 2026-08-16T04:45:19.959790Z

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 c57436ab-1069-42f2-8f43-267c0fe2c3f2 · outbound

This paper cites ACDC: A struc- tured efficient linear layer.

Block Circulant Adapter for Large Language Models ACDC: A struc- tured efficient linear layer

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.950642Z

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 eb633c16-c820-404a-bbf9-6bebfcc8d242 · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library.

Block Circulant Adapter for Large Language Models Pytorch: An imperative style, high- performance deep learning library

Reference 26

Resolution
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no resolver link, observed 2026-08-16T04:45:19.692149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b67e8aa5-a09e-47a1-a4a1-e1c8791c31d1 · outbound

This paper cites Sftc: Machine unlearning via selective fine-tuning and targeted confusion.

Block Circulant Adapter for Large Language Models Sftc: Machine unlearning via selective fine-tuning and targeted confusion

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.920674Z

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 e5744e1a-01ec-4ef4-a5ac-3de7c503238b · outbound

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

Block Circulant Adapter for Large Language Models SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 28

Resolution
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no resolver link, observed 2026-08-16T04:45:19.698606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 64fa876d-6e97-4e41-a9ba-ba0104f5872e · outbound

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

Block Circulant Adapter for Large Language Models Recursive deep models for semantic compositionality over a sentiment treebank

Reference 29

Resolution
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raw_fallback, observed 2026-08-16T04:45:19.911023Z

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 9177c659-eb84-49f3-8bef-1bc5d282865b · outbound

This paper cites Hashimoto.

Block Circulant Adapter for Large Language Models Hashimoto

Reference 31

Resolution
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no resolver link, observed 2026-08-16T04:45:19.708498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0340b812-c014-4e0f-9645-95bf292bba62 · outbound

This paper cites Learning compressed transforms with low displacement rank.

Block Circulant Adapter for Large Language Models Learning compressed transforms with low displacement rank

Reference 32

Resolution
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raw_fallback, observed 2026-08-16T04:45:19.886778Z

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 4f5f3bbc-1c2b-422b-9c04-615b0b9a53f3 · outbound

This paper cites Bow- man.

Block Circulant Adapter for Large Language Models Bow- man

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.877016Z

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 813ccce0-51e8-49a5-9164-6b39abe1a29a · outbound

This paper cites Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning.

Block Circulant Adapter for Large Language Models Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.720379Z digest=sha256:2246a1df709dfc87f60f002afaeb940543a32fcb2bc71a2a8565f68ac1b680f5

Observation 7b826a73-da10-4686-979a-e0c750263848 · outbound

This paper cites an unresolved cited work.

Block Circulant Adapter for Large Language Models Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:45:19.867652Z

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 62a36664-7151-47c3-8494-fd20e7af3d9f · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Block Circulant Adapter for Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 37

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.726847Z digest=sha256:f2d2c0109ff7925f3b5438b23ab3cf9cd84939e942c3aec1f137c923225e8178

Observation 45d2982f-e3fb-48f5-a08c-51fed9f92c28 · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

Block Circulant Adapter for Large Language Models ADADELTA: An Adaptive Learning Rate Method

Reference 38

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no resolver link, observed 2026-08-16T04:45:19.730337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d1da3424-54a4-4c07-a9a6-90e082cd203b · outbound

This paper cites Xing, Hao Zhang, Joseph E.

Block Circulant Adapter for Large Language Models Xing, Hao Zhang, Joseph E

Reference 40

Resolution
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raw_fallback, observed 2026-08-16T04:45:19.848014Z

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 d5ed896f-4392-4c97-b432-84b3383974fe · outbound

This paper cites Pre-trained Large Language Models Use Fourier Features to Compute Addition.

Block Circulant Adapter for Large Language Models Pre-trained Large Language Models Use Fourier Features to Compute Addition

Reference 41

Resolution
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no resolver link, observed 2026-08-16T04:45:19.739427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.739427Z digest=sha256:4d9f4f8ef62c9be42cd5b8c2dfca3b820d85b12fa7f29e0a2873c2ef494940c1

Observation f04a815c-03d8-4eba-ad4a-1d5cccdf4398 · outbound

This paper cites Circconv: A structured convolution with low complexity.

Block Circulant Adapter for Large Language Models Circconv: A structured convolution with low complexity

Reference 1988

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.968660Z

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 723873a5-9156-44fa-83b3-4741715bfd26 · outbound

This paper cites an unresolved cited work.

Block Circulant Adapter for Large Language Models Unresolved cited work

Reference 1994

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:45:20.090822Z

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=pdf_text observed=2026-08-16T04:45:19.619266Z digest=sha256:e4231407ff87deee73c22692ed6c7abad0501df5a4400e37a97b22469fb1af90

Observation 52c12372-4e8c-4ddd-b3b9-1feb324bf427 · outbound

This paper cites Automatic differentiation in pytorch.

Block Circulant Adapter for Large Language Models Automatic differentiation in pytorch

Reference 1999

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:19.689082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.689082Z digest=sha256:c5604ecdd84b7156fc71c55665041f51330b1fbc3b8e8749f7a8352176036d2f

Observation 56746bb2-859c-4a41-99c9-7dcfa2fabf45 · outbound

This paper cites Monarch: Expressive structured matrices for efficient and accurate training.

Block Circulant Adapter for Large Language Models Monarch: Expressive structured matrices for efficient and accurate training

Reference 2005

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.052287Z

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=pdf_text observed=2026-08-16T04:45:19.639999Z digest=sha256:3a477892c5788fb4084a469faa39f21324ea8e59ae03af9371a8d668508ecd8e

Observation 3cdc0956-4daf-43a2-950c-b75e50ddeb98 · outbound

This paper cites Theoretical properties for neural networks with weight matrices of low displacement rank.

Block Circulant Adapter for Large Language Models Theoretical properties for neural networks with weight matrices of low displacement rank

Reference 2012

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.858281Z

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=pdf_text observed=2026-08-16T04:45:19.733620Z digest=sha256:ec4c61160c2ba7ec124bbfa91c5c925373374abb0f56e198ee4bec22143fc3af

Observation 9fc4baff-e260-49b5-ab8f-17f8b528af3e · outbound

This paper cites Lst: Ladder side-tuning for parameter and mem- ory efficient transfer learning.

Block Circulant Adapter for Large Language Models Lst: Ladder side-tuning for parameter and mem- ory efficient transfer learning

Reference 2013

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.901599Z

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=pdf_text observed=2026-08-16T04:45:19.705374Z digest=sha256:9ef76ab1ac99c88beda9ef82fabc3c88771d97da10b3a4fe26115b1cce4deb45

Observation ddbd9f1c-0d32-4a41-b827-5a2faf9d855e · outbound

This paper cites Prompt sapper: a llm-empowered production tool for building ai chains.

Block Circulant Adapter for Large Language Models Prompt sapper: a llm-empowered production tool for building ai chains

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.070743Z

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=pdf_text observed=2026-08-16T04:45:19.630068Z digest=sha256:f813a2d37209e1d65a75ab67dd2f801d1ad9b68cbadc710af69325b8ecfdd64c

Observation d19729c2-8580-4f1c-95d2-06ad7fa1a70f · outbound

This paper cites Discrete-time sig- nal processing.

Block Circulant Adapter for Large Language Models Discrete-time sig- nal processing

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:19.941164Z

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=pdf_text observed=2026-08-16T04:45:19.685980Z digest=sha256:29ab0e4b96e2be6a9bf336db7bcef1980bac9b473b9b169b92351a39af2a9e6d

Observation aabf857d-9829-4a2d-aedc-745a4e4fa8a8 · outbound

This paper cites An exploration of parameter redundancy in deep networks with circulant projections.

Block Circulant Adapter for Large Language Models An exploration of parameter redundancy in deep networks with circulant projections

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.080859Z

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=pdf_text observed=2026-08-16T04:45:19.626801Z digest=sha256:1e1ebcaed026159bc9ff12cb30642add243cfdf9e408a15018ad765bea08a903

Observation 8081b634-e061-4d71-8791-7a2f6b382120 · outbound

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

Block Circulant Adapter for Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:19.714292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.714292Z digest=sha256:d39e734de907ccea8ae6a7df021c41bb00edf0038bd03172612d0aa4a528e13e

Observation ee96c7b0-fcf7-4939-9624-ec6ba32c9c18 · outbound

This paper cites Circnn: accelerat- ing and compressing deep neural networks using block- circulant weight matrices.

Block Circulant Adapter for Large Language Models Circnn: accelerat- ing and compressing deep neural networks using block- circulant weight matrices

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.028909Z

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 ff19d1d5-dd01-4b22-a6a8-574678c77a96 · outbound

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

Block Circulant Adapter for Large Language Models SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:19.623046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6dde3138-43ee-4ac5-84a5-06470c44a333 · outbound

This paper cites The pascal recognising textual entailment challenge.

Block Circulant Adapter for Large Language Models The pascal recognising textual entailment challenge

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.061172Z

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 45d60b05-1f50-4393-b38f-22970461b74e · outbound

This paper cites Qlora: Efficient fine- tuning of quantized llms.

Block Circulant Adapter for Large Language Models Qlora: Efficient fine- tuning of quantized llms

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:19.642973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b11c3d1f-9a24-4724-b243-43150a6b3f90 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Block Circulant Adapter for Large Language Models Parameter-efficient transfer learning for nlp

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:19.661326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:45:19.661326Z digest=sha256:82c1928ac56e2bd29fe97be4ad871859fd313cb441a50301a7d36dfc2b621e7a

Observation 1a7b165b-ffd5-4841-bcec-00052eb1b6c9 · outbound

This paper cites Learning long-term dependencies with gradient descent is difficult.

Block Circulant Adapter for Large Language Models Learning long-term dependencies with gradient descent is difficult

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:45:20.101109Z

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=pdf_text observed=2026-08-16T04:45:19.615716Z digest=sha256:8eba75522a8e26a7c84f1b5377d39f2f892378795e384ed1127c88d9e4ff4415

Pith citing papers

Observation 92de2867-6c86-48d2-a064-6aae1e2cf772 · inbound

Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning cites this paper.

Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning Block Circulant Adapter for Large Language Models

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:13:44.704708Z

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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