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Paper Citation Record · LEDGER

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding

As of 13 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2606.03539.

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

pith.paper-citation-record.v1
2606.03539 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T11:14:30.556120Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

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  • verified fuzzy0
  • unresolved19
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  • malformed identifier0
  • metadata mismatch1

External citation measurements

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Outbound references

Observation e48bb2b2-9a0a-4a4b-b6fc-c2fdbe01636b · outbound

This paper cites Where does it exist: Spatio-temporal video grounding for multi-form sentences,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Where does it exist: Spatio-temporal video grounding for multi-form sentences,

Reference 1

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:844d7a1d2c1bee6ef4d7c9db1d638d7fe295da20f582a475cb6d572da9a41f80

Observation 3f9d4645-50cb-4ccd-a328-2955fb581b75 · outbound

This paper cites End-to-end object detection with transformers,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding End-to-end object detection with transformers,

Reference 2

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:1df448432868fda3720cb239ed9be702dc1d1fdb71594c2758aa7a3f1bf9d66e

Observation 4122c895-3ee0-4248-ab2e-b91b13d902d6 · outbound

This paper cites Context-guided spatio-temporal video grounding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Context-guided spatio-temporal video grounding,

Reference 3

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Observation d2d66a14-a6cd-4bbc-a276-508bc2ab8df0 · outbound

This paper cites Knowing your target: Target-aware transformer makes better spatio-temporal video grounding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Knowing your target: Target-aware transformer makes better spatio-temporal video grounding,

Reference 4

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:efa15e6fd5174d180f6eb5ca5c1167226d704e611e6edbdc6e5bea1cd7e75cb2

Observation c3d6f262-29b6-4946-836b-9fbf75eaf953 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Lora: Low-rank adaptation of large language models,

Reference 5

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Observation fb48f617-81fe-4957-abb8-29df9a9b77fe · outbound

This paper cites Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding

Reference 6

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arxiv_id, observed 2026-07-02T02:06:26.947126Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c5b4a982-bebe-4533-a967-d5f1d30e049f · outbound

This paper cites Human-centric spatio-temporal video grounding with visual transformers,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Human-centric spatio-temporal video grounding with visual transformers,

Reference 7

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:43592e5a4afd91c9ad0c717ebd98b82684d47503b22700e29131693cd2faa133

Observation f13a1273-5734-413e-8d18-a69e2269e951 · outbound

This paper cites Stvgbert: A visual-linguistic transformer based framework for spatio-temporal video grounding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Stvgbert: A visual-linguistic transformer based framework for spatio-temporal video grounding,

Reference 8

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Observation 91cf645a-2827-4ae8-906e-1b8ef5968439 · outbound

This paper cites Tubedetr: Spatio-temporal video grounding with transformers,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Tubedetr: Spatio-temporal video grounding with transformers,

Reference 9

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Observation bcf252dd-3ed1-48c1-806f-d311c068030a · outbound

This paper cites Embracing consistency: A one-stage approach for spatio-temporal video grounding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Embracing consistency: A one-stage approach for spatio-temporal video grounding,

Reference 10

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Observation f2283f40-9971-4b32-a6f1-f243cbb8ce11 · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Parameter-efficient transfer learning for nlp,

Reference 11

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Observation b2540c0b-f090-42b1-a433-11892bce7e87 · outbound

This paper cites Visual prompt tuning,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Visual prompt tuning,

Reference 12

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:292de2d1e577a8e01a79dcf21f8d9cd9034c0a6b47d98d8250ce9649147023cd

Observation 16e9b53d-7fa4-4203-8c5c-aeba34c1f237 · outbound

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

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Adaptive budget allocation for parameter-efficient fine-tuning,

Reference 13

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:4a2643270991a8c40ef7f2e3dc0d760aca5e242da19276fc652e40436fa3466d

Observation eb705650-a9d5-4a74-ab81-cccfd1e15e99 · outbound

This paper cites Dora: Weight-decomposed low- rank adaptation,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Dora: Weight-decomposed low- rank adaptation,

Reference 14

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Observation b59bcfe2-48a5-4dad-a7d9-67f4003be12d · outbound

This paper cites Training networks in null space of feature covariance for continual learning,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Training networks in null space of feature covariance for continual learning,

Reference 15

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:6371fd8cb7aac24bb1a50e0d4a58ebf3ed5fc9af5ed3121fc1201de7321e1d08

Observation cf412c52-24d9-4eec-bc02-998690b5cf77 · outbound

This paper cites Alphaedit: Null-space con- strained knowledge editing for language models,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Alphaedit: Null-space con- strained knowledge editing for language models,

Reference 16

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Observation 9b9d7254-2805-43ae-bd10-22dab4155469 · outbound

This paper cites Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning

Reference 17

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arxiv_id, observed 2026-07-28T00:21:30.371308Z

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Observation b86d7a75-5982-4af6-af5b-aed519b71bd6 · outbound

This paper cites Flylora: Boosting task decoupling and parameter efficiency via implicit rank-wise mixture-of-experts.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Flylora: Boosting task decoupling and parameter efficiency via implicit rank-wise mixture-of-experts

Reference 18

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arxiv_id, observed 2026-07-02T02:06:26.939163Z

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:49b609a2e3026b87b9b0653ae2ee6df8ec3301f02ebb235c2493a4ec0e113c08

Observation 04334199-c76d-4078-88af-02bd8dcd4854 · outbound

This paper cites Deep residual learning for image recognition,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Deep residual learning for image recognition,

Reference 19

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Observation 83af5585-9ed0-4b45-92c5-c2c76adc81ab · outbound

This paper cites Video swin transformer,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Video swin transformer,

Reference 20

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:28f00fce67e726c24a982849bddb77c83a908b08f606e3beedb4e26434a2d19d

Observation 542569f7-1ab2-451f-b48f-0c493e957716 · outbound

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

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 21

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local_arxiv, observed 2026-07-02T02:06:26.943215Z

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:75d51c4628dfd1182862e6e1d6e7811f40bbd178820ccd11dc948d88a6fc03ba

Observation 359a82ff-a354-4692-8952-313befab99a7 · outbound

This paper cites Mdetr-modulated detection for end-to-end multi-modal understanding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Mdetr-modulated detection for end-to-end multi-modal understanding,

Reference 22

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:3ac6004764cd1c5912291979038a83b45e24222fd1ce49a78ca5538df08e81ac

Observation a06b8aeb-401b-4e8a-afeb-f022924fa604 · outbound

This paper cites Decoupled Weight Decay Regularization.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Decoupled Weight Decay Regularization

Reference 23

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local_arxiv, observed 2026-07-02T02:06:26.931089Z

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source=pdf_text observed=2026-06-28T11:14:30.556120Z digest=sha256:85c7a625a4128932ab3c5fa95269583f4f9d33fc6f5476a99666df4ead311c7f

Observation da3cb052-59fc-4d5e-98eb-8191c605870d · outbound

This paper cites Collaborative static and dynamic vision-language streams for spatio-temporal video grounding,.

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding Collaborative static and dynamic vision-language streams for spatio-temporal video grounding,

Reference 24

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Pith citing papers

No inbound Pith citation observations are available.