Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:30:14.998791Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2507.10855.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:30:14.998791Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
58 of 58 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 9511c46e-1fea-4a3b-adb3-c6a4f55fc39f · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Decomposing and interpreting image representations via text in vits beyond CLIP
Reference 1
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Sparse Fine-Tuning of Transformers for Generative Tasks A fast iterative shrinkage- thresholding algorithm for linear inverse problems
Reference 2
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Sparse Fine-Tuning of Transformers for Generative Tasks Longformer: The Long-Document Transformer
Reference 3
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Sparse Fine-Tuning of Transformers for Generative Tasks Rep- resentation learning: A review and new perspectives
Reference 4
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Reference 5
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Reference 6
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Reference 9
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Sparse Fine-Tuning of Transformers for Generative Tasks Generating Long Sequences with Sparse Transformers
Reference 10
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Observation e8b053f3-b16f-4d1f-85f3-65e9c598153d · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks An image is worth 16x16 words: Trans- formers for image recognition at scale
Reference 11
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Sparse Fine-Tuning of Transformers for Generative Tasks Transcoders enable fine-grained interpretable circuit analy- sis for language models
Reference 12
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Observation 7f56e7ad-4ed9-49fd-879a-daa117a23228 · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks The Vendi Score: A Diversity Evaluation Metric for Machine Learning
Reference 13
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Observation 1a028349-fa93-4346-92c9-f99bbf7d92ae · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Svdiff: Compact param- eter space for diffusion fine-tuning
Reference 14
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Observation 7de6e6f4-2ea0-4c63-b085-3349a69f266c · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Conceptexpress: Harnessing diffusion models for single-image unsupervised concept extraction
Reference 15
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Sparse Fine-Tuning of Transformers for Generative Tasks Lora: Low- rank adaptation of large language models
Reference 16
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Sparse Fine-Tuning of Transformers for Generative Tasks SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
Reference 17
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Sparse Fine-Tuning of Transformers for Generative Tasks Text embed- ding is not all you need: Attention control for text-to-image semantic alignment with text self-attention maps
Reference 18
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Reference 19
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Sparse Fine-Tuning of Transformers for Generative Tasks An introduction to variational autoencoders
Reference 20
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Reference 21
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Sparse Fine-Tuning of Transformers for Generative Tasks Multi-concept customization of text-to-image diffusion
Reference 22
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Sparse Fine-Tuning of Transformers for Generative Tasks FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference
Reference 23
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Sparse Fine-Tuning of Transformers for Generative Tasks DoRA: Weight-Decomposed Low-Rank Adaptation
Reference 24
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Sparse Fine-Tuning of Transformers for Generative Tasks Re-Imagining Multimodal Instruction Tuning: A Representation View
Reference 25
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Sparse Fine-Tuning of Transformers for Generative Tasks CAME: Confidence-guided Adaptive Memory Efficient Optimization
Reference 26
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Sparse Fine-Tuning of Transformers for Generative Tasks Supervised dictionary learning
Reference 27
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Observation bb28413e-c0a7-476d-a41b-ae3380648e15 · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Reference 28
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Observation 9e79c806-f05c-446c-90c1-3fbdd0f7001d · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Con- tinual learning with filter atom swapping
Reference 29
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Sparse Fine-Tuning of Transformers for Generative Tasks Spatiotemporal joint filter decomposition in 3d convolutional neural networks
Reference 30
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Reference 31
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Reference 32
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Observation 047baf86-a9dc-4380-b604-eefe4fe28c9d · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks Coeff-tuning: A graph filter subspace view for tuning attention-based large models
Reference 33
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Reference 34
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Sparse Fine-Tuning of Transformers for Generative Tasks Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
Reference 36
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Reference 37
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Reference 38
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Sparse Fine-Tuning of Transformers for Generative Tasks Dcfnet: Deep neural network with decomposed convolutional filters
Reference 39
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Reference 40
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Reference 41
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Reference 42
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Reference 44
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Reference 46
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Reference 47
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Reference 48
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Reference 49
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Reference 50
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Reference 51
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Reference 52
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Reference 53
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Reference 54
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Reference 56
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Reference 57
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Observation a9bd85a6-a7e8-4dd8-88cf-71992dbb7594 · outbound
Sparse Fine-Tuning of Transformers for Generative Tasks A grey ⟨V ⟩ wolf plushie
Reference 58
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No inbound Pith citation observations are available.