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Paper Citation Record · LEDGER

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation

As of 22 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.25106.

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

pith.paper-citation-record.v1
2607.25106 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T01:22:28.834204Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation b5696181-1a07-4da3-b2b9-83a263b47bf9 · outbound

This paper cites Learning transferable visual models from natural language su- pervision,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Learning transferable visual models from natural language su- pervision,

Reference 1

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source=pdf_text observed=2026-07-31T01:22:26.977084Z digest=sha256:376de021197227a0c4334d7f53a70c0346d34235918d91d8732127fae5e163cb

Observation 672232e2-3319-4f88-b17b-7639c0ba09d1 · outbound

This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 2

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source=pdf_text observed=2026-07-31T01:22:27.059042Z digest=sha256:0608cd5e276e362d00706f3e3f7d0da642dccf20e10e2610bb9b83db42191248

Observation b488b456-8628-46c3-a6fd-31189e8658a3 · outbound

This paper cites Sed: A simple encoder-decoder for open-vocabulary semantic segmentation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Sed: A simple encoder-decoder for open-vocabulary semantic segmentation,

Reference 3

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source=pdf_text observed=2026-07-31T01:22:27.132701Z digest=sha256:10cd1577a0a4c98ec8f4b82df179f2c824b565fa6badbef0ca215a4b1c1fe1d3

Observation 1d5f39fa-ef67-471b-8a15-3a94e31c9068 · outbound

This paper cites Vlfm: Vision- language frontier maps for zero-shot semantic navigation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Vlfm: Vision- language frontier maps for zero-shot semantic navigation,

Reference 4

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source=pdf_text observed=2026-07-31T01:22:27.226781Z digest=sha256:549aa40c51ffffcf3793a7393a72c631f1d4748bd8dac34b816e1ef4132fc694

Observation e715036e-a79a-4c62-941e-724c6e8feacd · outbound

This paper cites Onemap to find them all: A spatial semantic map for multi-query object search,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Onemap to find them all: A spatial semantic map for multi-query object search,

Reference 5

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source=pdf_text observed=2026-07-31T01:22:27.323449Z digest=sha256:74a1bf0378d93c9f97395622a29e0b2be2affd73f33a412a36ae7435bea4b3ca

Observation aacd11c7-93f5-4197-8602-8e67b126a114 · outbound

This paper cites Search and detect: Training-free long tail object detection via web- image retrieval,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Search and detect: Training-free long tail object detection via web- image retrieval,

Reference 6

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source=pdf_text observed=2026-07-31T01:22:27.394012Z digest=sha256:2b4eed80854dd8ccce762241ffca48a74d22a89edb9d844c1b50fe95ebf3a79d

Observation 0fac7589-b6ec-43a8-893b-b7b12c239209 · outbound

This paper cites VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search

Reference 7

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source=pdf_text observed=2026-07-31T01:22:27.471673Z digest=sha256:b700ca3b4953941c25203b906c5646eb9a326015b782fa3b7f99e2b544a44190

Observation 90295b46-9461-4a6c-93bc-927502b16d0d · outbound

This paper cites Hm3d- ovon: A dataset and benchmark for open-vocabulary object goal navigation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Hm3d- ovon: A dataset and benchmark for open-vocabulary object goal navigation,

Reference 8

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source=pdf_text observed=2026-07-31T01:22:27.560293Z digest=sha256:365916793849a56e842f4a0cd8f866dbae42aaca582e208d10f7feb6688f353c

Observation 6a7de46e-a258-44f2-ba91-1bdd1a663f5b · outbound

This paper cites Habitat synthetic scenes dataset (hssd-200): An analysis of 3d scene scale and realism tradeoffs for objectgoal navigation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Habitat synthetic scenes dataset (hssd-200): An analysis of 3d scene scale and realism tradeoffs for objectgoal navigation,

Reference 9

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source=pdf_text observed=2026-07-31T01:22:27.648071Z digest=sha256:79ad0340e76eb910aae0f35e2981628ffbbb6118cd5334b1679867ad0fa2b542

Observation 7728cbf4-ae68-4622-b951-764c898fe0c6 · outbound

This paper cites Matterport3d: Learning from rgb- d data in indoor environments,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Matterport3d: Learning from rgb- d data in indoor environments,

Reference 10

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source=pdf_text observed=2026-07-31T01:22:27.743675Z digest=sha256:4d8b7f19f1c0fd9c9c9af284b591d047749889718a1127a1ea0073e7b87bea43

Observation 5547500f-bfb0-48f2-bbc9-27083b423a05 · outbound

This paper cites Gibson env: Real-world perception for embodied agents,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Gibson env: Real-world perception for embodied agents,

Reference 11

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source=pdf_text observed=2026-07-31T01:22:27.825174Z digest=sha256:ac7bc5d506949dfd8aa9499b6323616d295ff9f41f84ededc7e12ab3fe586bd4

Observation 6b6d219a-2dbd-415e-bc05-361036bdce06 · outbound

This paper cites Vlmaps: Vision- language maps for robot navigation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Vlmaps: Vision- language maps for robot navigation,

Reference 12

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source=pdf_text observed=2026-07-31T01:22:27.909867Z digest=sha256:fd14b193748979f879597b45ed6bc42d9c35bcc4a7cf60a36c553c7be33ba0b6

Observation 5b0f8e9a-dcf4-428f-92c9-3c6bf2f28343 · outbound

This paper cites Openfusion: Real-time open-vocabulary 3d mapping and queryable scene representation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Openfusion: Real-time open-vocabulary 3d mapping and queryable scene representation,

Reference 13

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source=pdf_text observed=2026-07-31T01:22:27.990458Z digest=sha256:20a7a4b04e93848ddfbe40d0da19bb4509ce9fe3fb6313c0450e8835d4591745

Observation 42b7101f-8544-4714-b9c1-b50f94c558b1 · outbound

This paper cites Sigmoid loss for language image pre-training,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Sigmoid loss for language image pre-training,

Reference 14

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source=pdf_text observed=2026-07-31T01:22:28.073835Z digest=sha256:77b85836130dc5905ec476efe568eef44b552152920ae2e6bb68f88911ae43dc

Observation 5a955a01-5382-4560-b98a-d28cfd205558 · outbound

This paper cites Lseg: Language-driven semantic segmentation,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Lseg: Language-driven semantic segmentation,

Reference 15

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Observation 6a40bad8-e1a5-48f6-bac8-d767f5c7d02c · outbound

This paper cites Openscene: 3d scene understanding with open vo- cabularies,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Openscene: 3d scene understanding with open vo- cabularies,

Reference 16

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source=pdf_text observed=2026-07-31T01:22:28.223942Z digest=sha256:ce93dfb1938df895e379eec2baed9d5ba2429445e258d632ae83e3c2747fdd07

Observation b41b9817-993f-4787-b18e-34e09cd360ce · outbound

This paper cites Scaling open-vocabulary object detection,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Scaling open-vocabulary object detection,

Reference 17

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source=pdf_text observed=2026-07-31T01:22:28.284627Z digest=sha256:d33f386c1c2a2c849624deb3620467429d639ebc6cdf41575c479c412e0d8cda

Observation f9a3964a-a7f5-4e48-ba50-c30a60a33627 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Grounding dino: Marrying dino with grounded pre-training for open-set object detection,

Reference 18

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source=pdf_text observed=2026-07-31T01:22:28.384138Z digest=sha256:91a025f018c581b70ff1cee2c99a3db4e8a0a69ab18bb352f25acdcd010d6fb5

Observation 952672ad-c996-46ee-b52f-e22c9b48f678 · outbound

This paper cites Yolo- world: Real-time open-vocabulary object detection,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Yolo- world: Real-time open-vocabulary object detection,

Reference 19

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Observation 693be27e-1019-40db-b30e-4f4a147fcfd6 · outbound

This paper cites Deep long- tailed learning: A survey,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Deep long- tailed learning: A survey,

Reference 20

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source=pdf_text observed=2026-07-31T01:22:28.558965Z digest=sha256:8c788a2d8816a3a4e019aeca0cd2f45bfa09e6f8157e193601a0139c4f68b607

Observation 7eabeac9-7e4c-408d-92a9-4d8eb7e6d13d · outbound

This paper cites Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

Reference 21

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source=pdf_text observed=2026-07-31T01:22:28.701677Z digest=sha256:9126895fe58fbd7ea720e1820234d7614d9f78f10a86c1dd27da7f4fcbd1550a

Observation bdf6ba2f-a306-409a-b198-35364d737d9c · outbound

This paper cites Zson: Zero-shot object-goal navigation using multimodal goal embed- dings,.

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation Zson: Zero-shot object-goal navigation using multimodal goal embed- dings,

Reference 22

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source=pdf_text observed=2026-07-31T01:22:28.834204Z digest=sha256:f913c8978d98cecd5533edeeead74e45aebfdd8f47c33a404bbd990ab7e1ed90

Pith citing papers

No inbound Pith citation observations are available.