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Paper Citation Record · LEDGER

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training

As of 3 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2604.06836.

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

pith.paper-citation-record.v1
2604.06836 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T18:49:40.758234Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:54:47.776037Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

  • verified exact15
  • verified fuzzy4
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c313185b-0419-498d-ae35-cc38877b2d2d · outbound

This paper cites OCP Microscaling Data Formats (MX) Specification v1.0.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training OCP Microscaling Data Formats (MX) Specification v1.0

Reference 1

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verified fuzzy
raw_fallback, observed 2026-05-16T14:33:01.323907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 5d81f5aa-4b3c-4e2e-81f8-9e32be102c3a · outbound

This paper cites GPT-4 Technical Report.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training GPT-4 Technical Report

Reference 2

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verified exact
local_arxiv, observed 2026-05-10T23:55:49.346247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 173458db-6466-4e7d-a73d-6cb7fa115d87 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 3

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.313606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 1900575c-ce91-4ef9-87b2-81f5cb76aba6 · outbound

This paper cites 1999.Elements of information theory.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training 1999.Elements of information theory

Reference 4

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verified fuzzy
raw_fallback, observed 2026-05-16T14:33:01.318142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:d168292e7e9ce09c3c2ec9c519882a5e910a6ba8c8d93429ef99a1f2df2dfbb3

Observation b35a8172-04e3-4064-94fa-f70c1bbedace · outbound

This paper cites 8-bit Optimizers via Block-wise Quantization.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training 8-bit Optimizers via Block-wise Quantization

Reference 5

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verified exact
arxiv_id, observed 2026-05-10T23:55:49.370629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 1e857bed-2108-4f7a-bd00-9602a82ca82b · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 6

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.321381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation d6720081-1555-45b5-b8da-6970a590e90d · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 7

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raw_fallback, observed 2026-05-16T14:33:01.331356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:d493454219a9ab4c66cfe0e5e4bf481bb92d63927dc4dc6da2e2a4cac260d685

Observation 7c48cfdb-9015-4a02-aaad-9594a6c74cf3 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 8

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raw_fallback, observed 2026-05-16T14:33:01.326142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation fa243139-9f91-47eb-a2b8-c5d6fa7c85ac · outbound

This paper cites InProceedings of the IEEE/CVF international conference on computer vision.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training InProceedings of the IEEE/CVF international conference on computer vision

Reference 9

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verified fuzzy
raw_fallback, observed 2026-05-16T14:33:01.328744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:10bb5a6382a68b6639fb76e8b6a614e61e52fae7f14144cfbc980838914853c6

Observation 44d3966d-938c-43b3-8dad-b235fc4563d9 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 10

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raw_fallback, observed 2026-05-16T14:33:01.315778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation ba8fa601-3022-40d1-952d-145c890becd8 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 11

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raw_fallback, observed 2026-05-16T14:33:01.358797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 1e31ab96-ce91-475e-8898-20a5a0dda58d · outbound

This paper cites Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

Reference 12

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verified exact
arxiv_id, observed 2026-05-10T23:50:57.041214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 61c01a40-d29a-4e39-a9ba-f72cc79ca65e · outbound

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

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:26:21.985634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:ad56c82ed46770e9d147a27941f794227ad2061933cb3fd5c01e463ee3374cd6

Observation 26993bbf-bad5-40f4-a455-90255b8148a2 · outbound

This paper cites Decoupled Weight Decay Regularization.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Decoupled Weight Decay Regularization

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-05-10T23:55:49.394539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:b4201275d4f920d49eca7027a808098e1548f01717d9e2f46c5ce6d4b2bd692a

Observation 29c2f059-f440-40a5-b1a4-5624540182f1 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 15

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unresolved
raw_fallback, observed 2026-05-16T14:43:01.227693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:40abefc17fa0ef94161f5b3a654964d0ea3f1d204cfcc446cb396191f912005b

Observation 1d293173-3f92-480b-bddd-e6d3bcc2850b · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:11:43.638959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation f49e8b6a-f5a7-4fd1-bd91-18ebadd9237a · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 17

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unresolved
raw_fallback, observed 2026-05-16T14:43:01.225804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 3572185c-7927-4f2f-8418-151fc6a1d0a6 · outbound

This paper cites FP8 Formats for Deep Learning.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training FP8 Formats for Deep Learning

Reference 18

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verified exact
arxiv_id, observed 2026-05-15T09:47:03.886089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:5639e56fb28dbd6f13b55152d4e3f9bfff1b4e2ca4f068287e8a8c4f0c15a545

Observation f488cd5d-bdde-4031-858b-8f2ba01d7cf2 · outbound

This paper cites 2022–2024.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training 2022–2024

Reference 19

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verified fuzzy
raw_fallback, observed 2026-05-16T14:43:01.223684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:4b18da1cf8cdab9f652b0797c035b4688997779518e1e04174e391fe678d0b2e

Observation ba2c79a2-c796-41fe-afa2-fa62c34b4a6d · outbound

This paper cites Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:50:57.115470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 67749d3b-6fa8-4d43-8816-c7b4b9de020c · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 21

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raw_fallback, observed 2026-05-16T14:33:01.344325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 22d8d1f1-d258-4dd5-ae91-cfc4d2cca169 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 22

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raw_fallback, observed 2026-05-16T14:33:01.347223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 1c1666d1-a365-499e-9fe6-6fc438825396 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Code Llama: Open Foundation Models for Code

Reference 23

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verified exact
local_arxiv, observed 2026-05-10T23:50:57.052999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:82571ed42f70f2a3640a51781ecf8a36b0ad5f428dfdfa78214dd2ac3fc931ae

Observation a4fa52f5-4a64-4eee-90fd-b023ad987cb9 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 24

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raw_fallback, observed 2026-05-16T14:33:01.350095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:b9000ad0eced619811d6b32a4bed1d4f269aa7cae43aee7d6b48bdb66843329e

Observation e0fb67f7-4eca-4421-beb4-7905dc0dad3b · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 25

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raw_fallback, observed 2026-05-16T14:33:01.353117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 78db408b-f14e-4e85-8158-3dd1ee08552e · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 26

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verified exact
arxiv_id, observed 2026-05-10T23:50:57.060744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation a7e7f8c6-a30f-4213-9965-b0a497d2fa30 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 27

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.355855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 274c7201-6ab6-434f-97ab-5ca543a95a17 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.339240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 1410c832-e6e5-4689-a901-ef5d4e27045d · outbound

This paper cites Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization

Reference 29

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verified exact
arxiv_id, observed 2026-05-10T23:50:57.109952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation a6a56ddf-cdc2-45e8-995f-07274a4734be · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 30

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raw_fallback, observed 2026-05-16T14:33:01.341420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 29317db9-25e8-482b-b93c-4315196e1aa6 · outbound

This paper cites BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization

Reference 31

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verified exact
arxiv_id, observed 2026-05-10T23:50:57.088595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:ef06e9881b6386a8b12c0934105dd11b1f034ac4fe08c879f5309b865434e7b3

Observation d2e3be07-b002-47bc-93d3-667347d1e158 · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 32

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.334042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation fa3f298a-1c83-4324-87d8-926b0c8df63f · outbound

This paper cites an unresolved cited work.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Unresolved cited work

Reference 33

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unresolved
raw_fallback, observed 2026-05-16T14:33:01.336729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation aeceb0e6-5386-4b6e-800e-8555f3982c52 · outbound

This paper cites Adam-mini: Use Fewer Learning Rates To Gain More.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Adam-mini: Use Fewer Learning Rates To Gain More

Reference 34

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verified exact
arxiv_id, observed 2026-05-10T23:55:49.411139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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Observation 10ebd6c7-9b4d-4d50-8f16-5339a27965f5 · outbound

This paper cites Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:50:57.104621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:1af1c87a21d1a1cfb6cb1c45f77fb0404e3a264211ebdfb8205894916fe5c58a

Observation f1fc8388-31e1-4e25-a63e-e9953f03ebea · outbound

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

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:51:50.393199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:7f6ecb167d45f9b9fe394fb0fe82331e00bac91dd990fe37185dbf7567420654

Observation 854c4a3a-a5c3-4a44-bf91-fd23fbf6e76d · outbound

This paper cites A Survey of Large Language Models.

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training A Survey of Large Language Models

Reference 37

Resolution
metadata mismatch
local_arxiv, observed 2026-05-10T23:50:57.081052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T18:49:40.758234Z digest=sha256:81609faa4201495d622e00e9d424a9a2344a47b03de5b34fc76e992a051e8d67

Pith citing papers

Observation 35d96ce0-1d79-42b0-83e1-d93b44e760a7 · inbound

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection cites this paper.

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-02T07:54:47.776037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T07:54:47.776037Z digest=sha256:715fcdad2a3e0053bbe99a3fe5926f60d72796b810e63e72ad2e261d7543320d