Paper Citation Record · LEDGER

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2502.02972.

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

pith.paper-citation-record.v1
2502.02972 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:29:14.944575Z

measured 39 of 39 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.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact2
verified fuzzy18
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dfcc9967-2229-420c-a2aa-b3d884b7c84a · outbound

This paper cites Semi-supervised active learning for semantic segmentation in unknown environments using informative path planning,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Semi-supervised active learning for semantic segmentation in unknown environments using informative path planning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.533681Z

Source-reported events for the cited work

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

Observation 3c7e04f9-2119-47ae-8912-7f9ce6aa8898 · outbound

This paper cites Lightweight semantic segmentation network for semantic scene understanding on low-compute devices,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Lightweight semantic segmentation network for semantic scene understanding on low-compute devices,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.518099Z

Source-reported events for the cited work

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

Observation 2b0823e9-3e45-4094-a31d-08ba3676e1ad · outbound

This paper cites FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-09T10:29:15.152199Z

Source-reported events for the cited work

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

Observation 31c5ce28-1be1-4fa0-b286-51057cd676da · outbound

This paper cites Motionsc: Data set and network for real- time semantic mapping in dynamic environments,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Motionsc: Data set and network for real- time semantic mapping in dynamic environments,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.502477Z

Source-reported events for the cited work

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

Observation 7dfd1de9-5b93-45ad-9911-a7fd31fdf862 · outbound

This paper cites pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.485966Z

Source-reported events for the cited work

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

Observation 1a2ab054-1b63-4332-8124-fb69ab683570 · outbound

This paper cites Cekd: Cross-modal edge-privileged knowledge distillation for semantic scene understanding using only thermal images,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Cekd: Cross-modal edge-privileged knowledge distillation for semantic scene understanding using only thermal images,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.471006Z

Source-reported events for the cited work

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

Observation ecf2b56e-24da-421a-b0c4-f4744d7dfd36 · outbound

This paper cites Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.792526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5b39902-b2ab-4115-a948-cd5220846623 · outbound

This paper cites Under- standing bird’s-eye view of road semantics using an onboard camera,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Under- standing bird’s-eye view of road semantics using an onboard camera,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.455282Z

Source-reported events for the cited work

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

Observation 56c9d69a-cda8-4e98-9dfb-bc48b4ae18b8 · outbound

This paper cites Generalizable Autonomous Driving System across Diverse Adverse Weather Conditions.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Generalizable Autonomous Driving System across Diverse Adverse Weather Conditions

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T10:29:15.114985Z

Source-reported events for the cited work

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

Observation 59db7d5d-5739-4283-a677-5e15da736ee7 · outbound

This paper cites Towards compact autonomous driving perception with balanced learning and multi-sensor fusion,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Towards compact autonomous driving perception with balanced learning and multi-sensor fusion,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.808342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1ae3bbf-5b05-46ac-a95c-8dc900a48cb4 · outbound

This paper cites Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-09T10:29:15.092727Z

Source-reported events for the cited work

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

Observation 1f14fe9d-301d-4889-b7d0-8161407ca57b · outbound

This paper cites Segment Anything.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Segment Anything

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.818947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e45f044e-102c-4da8-b970-00199173b4f5 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.824130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c83a78c-839c-4b0e-bc4c-0ba2c9b7478a · outbound

This paper cites Carla: An open urban driving simulator,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Carla: An open urban driving simulator,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.430102Z

Source-reported events for the cited work

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

Observation a6b6c010-a191-4af1-b573-9817a052bf61 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.832984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c9de113-a94b-4c79-a4fb-8c2513e0f498 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Learning transferable visual models from natural language supervision,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.837873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bf32a30-4f75-480d-ad0c-657053fc37e5 · outbound

This paper cites Vilt: Vision-and-language transformer without convolution or region supervision,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Vilt: Vision-and-language transformer without convolution or region supervision,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.394788Z

Source-reported events for the cited work

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

Observation 5a422b35-3bfd-4b42-a604-4e0d789d4550 · outbound

This paper cites Vlmo: Unified vision-language pre- training with mixture-of-modality-experts,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Vlmo: Unified vision-language pre- training with mixture-of-modality-experts,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.379020Z

Source-reported events for the cited work

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

Observation e47951c7-a150-458b-80ec-3c6b47095261 · outbound

This paper cites Blip: Bootstrapping language- image pre-training for unified vision-language understanding and gen- eration,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Blip: Bootstrapping language- image pre-training for unified vision-language understanding and gen- eration,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.851509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7295529f-95a3-409e-929e-4bd76fe6c1c5 · outbound

This paper cites Lit: Zero-shot transfer with locked-image text tuning,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Lit: Zero-shot transfer with locked-image text tuning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.856350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba576611-5226-4ae2-ac76-daa16684796c · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.860765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2af0d4f8-21dd-44ce-820a-0304ae942299 · outbound

This paper cites A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.865485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fa3abd3-2c8c-452b-b164-0ef455583eb1 · outbound

This paper cites Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.870799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8b5b47d-e035-4972-a510-f42ced572335 · outbound

This paper cites Zero-shot open-vocabulary tracking with large pre- trained models,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Zero-shot open-vocabulary tracking with large pre- trained models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.335181Z

Source-reported events for the cited work

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

Observation a1fdfb13-62af-42b7-b6ac-0dd7c7e8695a · outbound

This paper cites Prompt, plan, perform: Llm-based humanoid control via quantized imitation learning,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Prompt, plan, perform: Llm-based humanoid control via quantized imitation learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.318407Z

Source-reported events for the cited work

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

Observation 9db8788d-3c96-4788-b889-1e0816698f6a · outbound

This paper cites Extracting Prompts by Inverting LLM Outputs.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Extracting Prompts by Inverting LLM Outputs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.884066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e8643b5-d7f3-4526-ab36-b143d6e49b8d · outbound

This paper cites Efficient Prompting for LLM-based Generative Internet of Things.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Efficient Prompting for LLM-based Generative Internet of Things

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.888993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d342d9ab-7d62-4f68-ab05-7b3cc407cdcc · outbound

This paper cites A simple zero-shot prompt weighting technique to improve prompt ensembling in text-image models,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator A simple zero-shot prompt weighting technique to improve prompt ensembling in text-image models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.303502Z

Source-reported events for the cited work

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

Observation 1e2df27d-6e39-4457-af29-dda49117160f · outbound

This paper cites Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.898680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbe02eb5-f5ad-4ff8-aed1-24a6a67252b0 · outbound

This paper cites Design guidelines for prompt engineering text-to-image generative models,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Design guidelines for prompt engineering text-to-image generative models,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.288189Z

Source-reported events for the cited work

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

Observation 08b173d0-42b2-47fc-80dc-f3fe37245cb1 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator The cityscapes dataset for semantic urban scene understanding,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.908652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65fb5263-df78-4547-a74b-cb3a893da0a1 · outbound

This paper cites Segmentation and recognition using structure from motion point clouds,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Segmentation and recognition using structure from motion point clouds,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.263843Z

Source-reported events for the cited work

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

Observation 2e247956-cf90-4bfd-9338-fd6eadb1a552 · outbound

This paper cites an unresolved cited work.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-09T10:29:15.247762Z

Source-reported events for the cited work

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

Observation 10199100-27ca-4efb-86da-809cbdf2abd0 · outbound

This paper cites The apolloscape open dataset for autonomous driving and its application,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator The apolloscape open dataset for autonomous driving and its application,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.232777Z

Source-reported events for the cited work

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

Observation ba85a5f6-9296-4027-9f00-005e511e0a37 · outbound

This paper cites Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.217132Z

Source-reported events for the cited work

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

Observation 252f2cb5-bc94-4ade-b462-1b3184fac473 · outbound

This paper cites Segnet: A deep convolutional encoder-decoder architecture for image segmentation,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Segnet: A deep convolutional encoder-decoder architecture for image segmentation,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.931254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 141bd968-ae3f-4167-89e5-1e1e85a9e6d4 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Encoder-decoder with atrous separable convolution for semantic image segmentation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.192146Z

Source-reported events for the cited work

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

Observation e21c183a-37de-4476-8935-089d9c3b7e72 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmen- tation with transformers,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Segformer: Simple and efficient design for semantic segmen- tation with transformers,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T10:29:15.177218Z

Source-reported events for the cited work

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

Observation 403c0e97-dcad-40c2-b37f-3792fdb16de8 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:14.944575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.