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Paper Citation Record · LEDGER

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

As of 9 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 11 inbound Pith citation observations for arXiv:2502.02723.

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

pith.paper-citation-record.v1
2502.02723 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:28:42.782058Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:52:34.945281Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

65 of 65 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 4bcfa074-0c5a-4cf5-9d92-75bf999d9168 · outbound

This paper cites Online embedding compression for text classification using low rank matrix factorization.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Online embedding compression for text classification using low rank matrix factorization

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:44.308721Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.728677Z digest=sha256:e72a184942410f18e395790d2e91c57891e560fef74640fd7c1d731d1185025f

Observation a2a31796-beb2-4155-aaf7-09f30101c05a · outbound

This paper cites GPT-4 Technical Report.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives GPT-4 Technical Report

Reference 2

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no resolver link, observed 2026-08-09T11:28:41.734065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.734065Z digest=sha256:c81bc3eab4d6418aaef5519716cbd94f47cc4983dc92ca2563de315785780571

Observation da0344b2-58d0-4440-af75-0c612c8bc739 · outbound

This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:41.738892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.738892Z digest=sha256:7206b77231aa7b98ce2c8aec39d0946993d488d14f3d2d2f5bb24f6659cd2c7a

Observation 7833c457-167b-46d3-bec5-b1bdcd40a65f · outbound

This paper cites Fluctuation-based adaptive structured pruning for large language models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Fluctuation-based adaptive structured pruning for large language models

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:44.257929Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.743565Z digest=sha256:70d2f97c820eca765cce49fc004065a0199d3de193cdecfb98a822eb61ad91b2

Observation 0203bb5c-415c-4efe-bc9c-2bd009ed3fb2 · outbound

This paper cites Fluctuation-based adaptive structured pruning for large language models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Fluctuation-based adaptive structured pruning for large language models

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:44.095705Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.748914Z digest=sha256:e6413f11fd1558b6c5f8708c48b1626a74fd43c55d8b2dce3e58fbe8f14f186d

Observation 42b9402e-2097-4547-a53f-760554f80f1a · outbound

This paper cites SliceGPT: Compress Large Language Models by Deleting Rows and Columns.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Reference 6

Resolution
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no resolver link, observed 2026-08-09T11:28:41.753549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.753549Z digest=sha256:f51f5950bda19c9438da77eb6ba31c56158a022d35619f49e95d76b1e78c3485

Observation b484d0ed-0e07-4151-b346-896ffe71afee · outbound

This paper cites Polycystic kidney disease.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Polycystic kidney disease

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.990652Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.759004Z digest=sha256:051bd5a735b64789f0d42f03ab18e9002cbb45a160ba42ed840b35c84e295d3a

Observation 5512a3b1-a4b1-47ef-82e1-d273f7f9c1a9 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Piqa: Reasoning about physical commonsense in natural language

Reference 8

Resolution
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no resolver link, observed 2026-08-09T11:28:41.789022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.789022Z digest=sha256:61e6c4fead639f0f49e828d549e63f87baf81644db972557709805bbd9b0dab2

Observation ed1371eb-c2ab-4243-bcfe-57627e32097c · outbound

This paper cites Compression of facial images using the k-svd algorithm.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Compression of facial images using the k-svd algorithm

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.948695Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.806167Z digest=sha256:e5ce0dce0406f9a090a94d6956fb666de32597321a3dbe565ca511a685acb593

Observation 4da6f7cc-d993-4278-8550-cd787e359626 · outbound

This paper cites Model compression.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Model compression

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:41.837530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.837530Z digest=sha256:41cc3f6fe0890b6b94270d2de14de8ac17480bfd55f93a6faee4680149fe00ac

Observation 4afa722c-74af-4adc-871c-ecbcacd4724a · outbound

This paper cites AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search

Reference 11

Resolution
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no resolver link, observed 2026-08-09T11:28:41.876800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.876800Z digest=sha256:7f12acc2fba26d3c5859a51de64c7d9331e6adc6827ba136279e5f7fb1df0a64

Observation 40154a49-5c52-43aa-a8c7-634c46894495 · outbound

This paper cites Groupreduce: Block-wise low-rank approximation for neural language model shrinking.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Groupreduce: Block-wise low-rank approximation for neural language model shrinking

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.920828Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:41.912377Z digest=sha256:d9c4ee0ab8a7fabe7ad1ad9dafdc1db9d6325a050057130ea3d8a76679d2f118

Observation ff14f3dc-5d70-4473-addd-62db01879b37 · outbound

This paper cites A Survey of Model Compression and Acceleration for Deep Neural Networks.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:41.989055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:41.989055Z digest=sha256:65e9b5eb9b31245d9cecf9612b1f6f75c632406570ab763ee906caf9d0f68efd

Observation 6cd99a94-218e-4a1a-8a3c-b6aa330be97a · outbound

This paper cites A comprehensive survey on model compression and acceleration.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A comprehensive survey on model compression and acceleration

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.904776Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.010396Z digest=sha256:022e4430717e8283ed410056650bd237e151518a61b528d983c606c758912807

Observation 17a68406-e469-42a8-9aeb-d2e05f9f120a · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.015659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.015659Z digest=sha256:215e75951461af9d2d471d363a85f42e2408008bae8df1bac9948739ed0e8453

Observation e5af80f8-d349-41bc-881a-29e9621b66b2 · outbound

This paper cites Exploiting linear structure within convolutional networks for efficient evaluation.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Exploiting linear structure within convolutional networks for efficient evaluation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.887379Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.020616Z digest=sha256:2a696cd11b11ae22e7d14230b1043662f135e6cd13802d44d019bc13332af35d

Observation 28820110-367f-46d4-9496-debfceb6c155 · outbound

This paper cites Everybody prune now: Structured pruning of llms with only forward passes.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Everybody prune now: Structured pruning of llms with only forward passes

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.025275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.025275Z digest=sha256:5f0e76e111c6bad2ead71a35ab4d2fda5e797f9f5d81c73e5714069a56c6e519

Observation 3996e979-36db-481d-b3a9-da6aef92a1f2 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Qlora: Efficient finetuning of quantized llms

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.136930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.136930Z digest=sha256:614a92e40d4672e52ebd01030e425ccc0d9a5a5f7b418d6e2f1884e590b30c77

Observation d5b6d554-3a1e-418c-a4a2-e6743113ece2 · outbound

This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Sparsegpt: Massive language models can be accurately pruned in one-shot

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.142052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.142052Z digest=sha256:0121e654508a8f83e370aab369dbe383f8978db5166e1c68994e2f90b7755b6c

Observation b8bab2db-b79a-4cbe-bf6b-76822a4b1ee8 · outbound

This paper cites Optq: Accurate quantization for generative pre-trained transformers.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Optq: Accurate quantization for generative pre-trained transformers

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.848589Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.147686Z digest=sha256:cff721f94145a2f3a53bdce5cb2600c247a3edc0bd2fe6ca5f3be88fc73d8478

Observation e9d88207-bb64-4067-b9e4-e644b1cb0063 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.151994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.151994Z digest=sha256:089ba03db1bd745272912c8b94555ce6ef0262a4bbff53af3cad60e9e5713270

Observation 05f0db00-f88c-4cbf-a9b9-2b83c3b97105 · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A framework for few-shot language model evaluation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.156513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.156513Z digest=sha256:634f91ba1d1a7e5e770f1e93f5acdbe25fd3bdd43057fddb96eb18dcd0d966da

Observation 5e1d1039-9846-4277-bd6a-c538d66f4a71 · outbound

This paper cites An efficient svd-based method for image denoising.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives An efficient svd-based method for image denoising

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.821404Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.160954Z digest=sha256:46fa63ec55b075f1f9cd47016c7cf2383c34fa3ad45d4fd9f81ba78044167a03

Observation 100ecf27-ea29-424d-afe9-6b052a2b3bf9 · outbound

This paper cites Dynabert: Dynamic bert with adaptive width and depth.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Dynabert: Dynamic bert with adaptive width and depth

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.804535Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.165375Z digest=sha256:c7c0b70e25c686629ad92f18c5fa2b4f6205d35083dfdab277ca88043e2b3a79

Observation 12986e8d-83a8-470f-bd81-c000a674a273 · outbound

This paper cites Language model compression with weighted low-rank factorization.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Language model compression with weighted low-rank factorization

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.170042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.170042Z digest=sha256:1e8cd692fc41a979da98c5c73b73de3207adfd4e048d5f9bfa5fe34cad0421a8

Observation 96009f49-6cd5-44ba-a6bd-bb4868e36dea · outbound

This paper cites Speeding up Convolutional Neural Networks with Low Rank Expansions.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Speeding up Convolutional Neural Networks with Low Rank Expansions

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.174810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.174810Z digest=sha256:aa9b7cfbbdd201194286c970d06f5d96fa273a2c7393c5c97bfed7a7819160e2

Observation 0165c44b-07a6-4503-90cd-b7ff83e2112e · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives OpenVLA: An Open-Source Vision-Language-Action Model

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.179119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.179119Z digest=sha256:39dc38dd2395e98706eaddb9fdfe7343de9c0c18e4ac1c6bcb1387342fd546bc

Observation 8b308851-e505-4df8-ad27-7ad194f53a52 · outbound

This paper cites SqueezeLLM: Dense-and-Sparse Quantization.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives SqueezeLLM: Dense-and-Sparse Quantization

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.183775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.183775Z digest=sha256:f8c79ad1ecff8e91940f49af34449aa8104f61df9b1d872f10aad58dbf3adb38

Observation 77e05df3-c775-4879-adca-e1deb99f96dc · outbound

This paper cites The singular value decomposition: Its computation and some applications.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives The singular value decomposition: Its computation and some applications

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.787911Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.188513Z digest=sha256:15f9b0f0ebff57d5a808414d5c1bb14e0c86b017aed7b493bf3eb4cd5fc7efab

Observation 6755f68b-b791-4a9b-b8de-11ffd0f0b17a · outbound

This paper cites Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.193127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.193127Z digest=sha256:f4b1a01d50c0392bb7cebcbc29ed99e17cad44309f759b4caac9f4cb5e7d03d1

Observation ab67c8cd-a77d-486d-b086-0d449177f920 · outbound

This paper cites Mimo transmission over a time-varying channel using svd.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Mimo transmission over a time-varying channel using svd

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.770022Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.197485Z digest=sha256:36cc3c5256f1aa993bfe113ae2dda7314e3196d160e000b4cb114198e7ddaf9d

Observation eb3ebefa-7e85-4327-9f87-e76e23343974 · outbound

This paper cites LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.201982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.201982Z digest=sha256:5e1936f3388f096e1a73310356f9a350cb647df1d3841f8c1c794da8b6252245

Observation 541a9166-7dcd-4109-92cd-d50d1be7d776 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Awq: Activation-aware weight quantization for on-device llm compression and acceleration

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.227778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.227778Z digest=sha256:300a1e39f0c66a3832145b7683d5bb5d06b8cd610428798ca01ddc424b42d0a3

Observation 2100be7d-1f2e-4742-9b81-5802c6530901 · outbound

This paper cites Improved baselines with visual instruction tuning.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Improved baselines with visual instruction tuning

Reference 34

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unresolved
no resolver link, observed 2026-08-09T11:28:42.267896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.267896Z digest=sha256:8abe9103a410183b33e78154e0180ef40c129caf2e53c4f6ac0363d414f96b6f

Observation 0cf694df-be49-4cdf-9a0c-aaa4fea675c5 · outbound

This paper cites Llm-pruner: On the structural pruning of large language models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Llm-pruner: On the structural pruning of large language models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.371607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.371607Z digest=sha256:2c11c303b9222d422fc3e3090bb64bf43698437c76861e3272cf022bd6ef47ed

Observation 310550ea-1bc2-4bf2-9409-741cccc8435c · outbound

This paper cites Building a large annotated corpus of english: The penn treebank.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Building a large annotated corpus of english: The penn treebank

Reference 36

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source=arxiv_source observed=2026-08-09T11:28:42.431531Z digest=sha256:29dd245ca8d3ac65c375129720674824adcc656ca05612427754c59f8ac1f27e

Observation 06a0301e-2523-417f-a179-a8aba0ee0a1f · outbound

This paper cites Pointer Sentinel Mixture Models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Pointer Sentinel Mixture Models

Reference 37

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no resolver link, observed 2026-08-09T11:28:42.437017Z

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source=arxiv_source observed=2026-08-09T11:28:42.437017Z digest=sha256:82adaff11ac150022c7eddf76cef7e9e53abfe21638737204937ffa4ee622546

Observation b923d85f-0b51-486f-86b2-2e3ef19e8b9e · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 38

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no resolver link, observed 2026-08-09T11:28:42.441449Z

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source=arxiv_source observed=2026-08-09T11:28:42.441449Z digest=sha256:be77c019f34eb63406e10f9cb025bf5c8c47c7ca927cb57cb7d22e383f86ba70

Observation 01ec3da1-08d8-45c0-adfa-87b56b4d1b13 · outbound

This paper cites ACDC: A Structured Efficient Linear Layer.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives ACDC: A Structured Efficient Linear Layer

Reference 39

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no resolver link, observed 2026-08-09T11:28:42.446884Z

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source=arxiv_source observed=2026-08-09T11:28:42.446884Z digest=sha256:9d61302460ae8976c485080af5149540d1e8ac3dab8cae5237200f7b325468ae

Observation b0d85e89-1e63-4ad9-9db4-c8e7b8732f36 · outbound

This paper cites Image compression using svd.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Image compression using svd

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.709916Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.452103Z digest=sha256:c8a8c3655e8025da61136017aa19c8edece29e946602ab13071430be2220bc88

Observation 5ece4296-0a93-4dfa-9159-73f4a2b6d871 · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 41

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no resolver link, observed 2026-08-09T11:28:42.457003Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.457003Z digest=sha256:053e2aaa2f20acf78ad87571f37cade7811a9f238e862f4e76f06b8cf4c79299

Observation 9beb877d-15c1-413d-8a9e-664b27c79661 · outbound

This paper cites Matrix compression via randomized low rank and low precision factorization.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Matrix compression via randomized low rank and low precision factorization

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.693174Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.461944Z digest=sha256:1c06180b08b24d2900d93feaacf54a53475f24287b8956f17d8286f8636e1e5f

Observation d563c240-c76a-4cc3-aba1-c10f28543947 · outbound

This paper cites Compressing Large Language Models using Low Rank and Low Precision Decomposition.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 43

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no resolver link, observed 2026-08-09T11:28:42.466468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.466468Z digest=sha256:db0b5e1f0c114e1fd0126b83e6c917077ef63dc0206c412caf189373406f1754

Observation 13997ab6-c7a7-4675-88e2-d11a0b153672 · outbound

This paper cites Low-rank matrix factorization for deep neural network training with high-dimensional output targets.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Low-rank matrix factorization for deep neural network training with high-dimensional output targets

Reference 44

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no resolver link, observed 2026-08-09T11:28:42.471191Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.471191Z digest=sha256:9fbc7b53dfae4bbebd45219cf7f7e294e92d7e7f62bae94e389a24b7c935fc09

Observation 1e8d0440-62ab-4f58-9a92-2b2c330a4315 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Winogrande: An adversarial winograd schema challenge at scale

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.608732Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.475865Z digest=sha256:571cf31021933211609f72a09867c63940250ed13b2d518f5b135db9bd210788

Observation 434727a9-f935-42c4-ace9-b25fb353ac1d · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Winogrande: An adversarial winograd schema challenge at scale

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.556374Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.480731Z digest=sha256:ccf9a23a0958094c731441e6e064cb6efd24e7f4584c6ae6d626a968d8acb526

Observation af495976-c665-41ef-8997-8bd30f57575f · outbound

This paper cites The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction

Reference 47

Resolution
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no resolver link, observed 2026-08-09T11:28:42.485667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.485667Z digest=sha256:23f33255cd0081b5e66a4355624295eab33200c8d40271ad9a35f035938a6f84

Observation 1a0ce23c-c2e9-4648-8002-6bf5101d6af0 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A Simple and Effective Pruning Approach for Large Language Models

Reference 48

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no resolver link, observed 2026-08-09T11:28:42.490118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.490118Z digest=sha256:9b7ab6bd64a0542b71c20a071d17164ff6491d7fed64f13db3687a948765ac78

Observation f175828b-14e0-4991-83c7-a12f67c56d2b · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives LLaMA: Open and Efficient Foundation Language Models

Reference 49

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no resolver link, observed 2026-08-09T11:28:42.495068Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.495068Z digest=sha256:012a7307e0d9b618f8ff69ea2e74fd20e0897f37cda902011c1e928e045c2d91

Observation 9ce627bf-d948-46bd-841c-b01d331763aa · outbound

This paper cites Pufferfish: Communication-efficient models at no extra cost.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Pufferfish: Communication-efficient models at no extra cost

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.467239Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.499865Z digest=sha256:fa20c276ed60fe68fe93d35ddb11116a092761f0ae85d061eae4136b159a7301

Observation 992b39bd-bb94-44ea-b27b-3377db3fb089 · outbound

This paper cites Robust differentiable svd.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Robust differentiable svd

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.448641Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.504833Z digest=sha256:c52c9121aa1ec4a4a8f02330a932b6d1a25f3d8e45a2db87005c2f72f5ac9682

Observation 4d395912-3d91-429c-89e0-8e7b8e6dc102 · outbound

This paper cites SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression

Reference 52

Resolution
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no resolver link, observed 2026-08-09T11:28:42.509299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.509299Z digest=sha256:c38bcd944c81badc140c365f836b0ba23f8bc701a84a1791ed9686fd1f415bdb

Observation b22028f7-21fb-4373-a079-e19855b26f98 · outbound

This paper cites Candid covariance-free incremental principal component analysis.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Candid covariance-free incremental principal component analysis

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.432442Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.513999Z digest=sha256:6f623a42de2c6309426d063d1a14a97596e56a8683669a8e3dd5a6d20457edc7

Observation 2876c3e4-03ec-46ea-a200-02f8c261382b · outbound

This paper cites The devil is in the details --- W ikipedia , the free encyclopedia.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives The devil is in the details --- W ikipedia , the free encyclopedia

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.417085Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.518140Z digest=sha256:e627a2f274bbb83693852e8f83a3be342e9a8a077ac0d5bf036368a5dacc6024

Observation a60e0235-b8eb-4d4c-b462-f833dfa36b97 · outbound

This paper cites Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

Reference 55

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no resolver link, observed 2026-08-09T11:28:42.522131Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.522131Z digest=sha256:e6cd393cba2b5a3a2f7da067c3fd40f5a0ce62689381ea4eefa552a279faf8b6

Observation e64fc05a-cbf4-4b36-997d-ae8b8030e2fb · outbound

This paper cites ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models

Reference 56

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no resolver link, observed 2026-08-09T11:28:42.526356Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T11:28:42.526356Z digest=sha256:c52e0132b0cd744764947d0a6ec088612ef3acb4a2b5cdc271f7c57f5a93dcb9

Observation b7caf2f9-3571-4444-bfd4-1c7e1fcd5131 · outbound

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

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.570201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.570201Z digest=sha256:47dceb120ade2c1dc03a6964bf2583945c8a4982b03085b9d58016d2fd7e5bb4

Observation 458170ee-cc5f-458f-bb52-13d3f0d5936f · outbound

This paper cites LQER: Low-Rank Quantization Error Reconstruction for LLMs.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives LQER: Low-Rank Quantization Error Reconstruction for LLMs

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.604458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.604458Z digest=sha256:a79c0444e04ab8671a2fdff615dac936f96e78687acf81eaa5e55378e128abce

Observation 9ce77cd2-bdfe-4efb-8463-001cdf496660 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives OPT: Open Pre-trained Transformer Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.651631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.651631Z digest=sha256:1e7bde7a987fd91e87d5fd3db5310c1ed1343082e4436073da46d5346fdf3d53

Observation 67c7d24b-be20-4a98-91ab-a6d20a00a95d · outbound

This paper cites Accelerating very deep convolutional networks for classification and detection.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Accelerating very deep convolutional networks for classification and detection

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.400419Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.689485Z digest=sha256:3d1ab5f53e63acb079679f07f5182b4bc1244cfb1cb12a272b335f4b8d590a97

Observation 071b07a0-3070-4513-82a3-521419cfc3e7 · outbound

This paper cites A novel strategy for signal denoising using reweighted svd and its applications to weak fault feature enhancement of rotating machinery.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A novel strategy for signal denoising using reweighted svd and its applications to weak fault feature enhancement of rotating machinery

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:28:43.383862Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.737800Z digest=sha256:51ad4bc613216a53f3a7bb64ff5f09bb6cbf02c96a1e0a26794a4d1583018154

Observation abcd91fc-4b79-4145-b1bb-5df9c3215ade · outbound

This paper cites write newline.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives write newline

Reference 62

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unresolved
no resolver link, observed 2026-08-09T11:28:42.766523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.766523Z digest=sha256:43897371c169e06d46a5c1a33a8bb392b11051be527021cb8678b67d7ceb2479

Observation 320e95d5-70e1-47f3-918f-06ffaac58c5d · outbound

This paper cites @esa (Ref.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives @esa (Ref

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.772679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.772679Z digest=sha256:bf4c49ecdc9fbb0e6ef3a2b263d256dbe49ea1d037c52a05b53b5e6730628ac8

Observation 576de6e5-b7eb-4ed6-ae59-458640f03c8a · outbound

This paper cites an unresolved cited work.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Unresolved cited work

Reference 64

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no resolver link, observed 2026-08-09T11:28:42.777627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.777627Z digest=sha256:f5638b94d1ecd4568bcc476290d9e12f7f321f2f13eedf8942e7dade449a6464

Observation fc691c87-b253-4778-a693-499b3a43a523 · outbound

This paper cites an unresolved cited work.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Unresolved cited work

Reference 65

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unresolved
raw_fallback, observed 2026-08-09T11:28:43.335050Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T11:28:42.782058Z digest=sha256:45cb5b24693e52fcd421a1faf7ca7bcb530c70e3a20c522e23b6a370441936e5

Pith citing papers

Observation 92630c1d-d3a7-4d52-b8e5-590a396fc622 · 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 Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T10:52:15.105013Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-19T10:50:36.629493Z digest=sha256:8de4da19424e049e02c36696c2975f19b3dbaac0bc5fc076e64edf5369f0d7a3

Observation 80863ccb-f140-4e60-be2e-760954c897e0 · inbound

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision cites this paper.

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 62

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unresolved
no resolver link, observed 2026-08-05T22:52:34.945281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:52:34.945281Z digest=sha256:960d6a0be07243ac18e34735fdcd6dfee5277916d46214c15d1bd59e2269b359

Observation 7a7c3906-05eb-4b15-bd72-62c0f4f5af37 · inbound

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint cites this paper.

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 29

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unresolved
no resolver link, observed 2026-08-04T17:22:08.984558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:22:08.984558Z digest=sha256:fcbca1cbe5bb03c848f96a90b789fd3ff1973f5a3fb19e33505197eef1e65911

Observation 1a9c3d5e-6a79-4555-aca3-7d9f1d6ac06d · inbound

NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium cites this paper.

NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:52:21.828106Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-18T02:51:19.275111Z digest=sha256:10d0a03f6e4a34740475642510eb3610dc75e88a75914671fd66ad5677be6656

Observation fc3fe965-3261-4108-8a38-d6be2b72e2df · inbound

Different Prompts, Different Ranks: Prompt-aware Dynamic Rank Selection for SVD-based LLM Compression cites this paper.

Different Prompts, Different Ranks: Prompt-aware Dynamic Rank Selection for SVD-based LLM Compression Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:41:33.281262Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-12T02:22:51.541981Z digest=sha256:855c76c4805b27fe2eb0465a950473d79414b71cdb112e17ae6c0f57f6d4c3ee

Observation 780a5aed-363f-4d75-b1f9-680ffc603211 · inbound

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models cites this paper.

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:03:17.841732Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-20T13:02:08.337788Z digest=sha256:042f9adc529a63c36ff337f4a8732ddfb5011850f30123813e29151628253ee7

Observation 790cbab5-caf8-42f9-8ded-dd198d1df81e · inbound

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation cites this paper.

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:02:34.643744Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-28T18:55:51.474956Z digest=sha256:c5d5a19e19b79ca8638bb1c1c07c18c2b16e1339bd70f5836fe2ac2cc965d53d

Observation 15e703f2-3558-44de-9f52-1ba3b8efc1fa · inbound

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models cites this paper.

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:12:34.654011Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-28T19:09:29.347284Z digest=sha256:13b1810ce5c00599ad809c07a1e6280b11f8f03a64557e02f6535bc20519ca3a

Observation 8cb8d725-9f22-4289-8845-758fa7265c5e · inbound

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression cites this paper.

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:46:26.847497Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-28T11:31:25.851340Z digest=sha256:0f352ec2ab40699dc1e9a4f908bd3e9467796a3a3bbbdf626b096267c453073c

Observation 469c2b70-0a88-446a-a3a9-ffb4dfce1e3d · inbound

SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices cites this paper.

SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-27T22:11:20.856484Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-27T22:04:32.524875Z digest=sha256:28ecfb8be6c2e816a089f706719df164a5f3fc1cc7a0dd98ea9dc101f66f1d81

Observation 91e5a9e7-e2ac-4db5-9dec-69fe05602ad9 · inbound

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression cites this paper.

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-12T05:11:18.690792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T05:11:18.690792Z digest=sha256:1770c289a79e28790429f3f6fc27ef513718d1898e392191ecb2bb2f0764c4f8