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Paper Citation Record · LEDGER

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding

As of 19 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2412.02449.

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

pith.paper-citation-record.v1
2412.02449 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:32:13.335331Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy25
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 63a0e451-30d4-42b3-9d0d-e132025f7735 · outbound

This paper cites Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collab- oration 0,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collab- oration 0,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-11T23:32:14.042775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation afbb85dc-c3fe-49f3-9280-cbed1e007a00 · outbound

This paper cites Co-fusion: Real-time segmentation, tracking and fusion of multiple objects,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Co-fusion: Real-time segmentation, tracking and fusion of multiple objects,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-11T23:32:14.028709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2bafc6da-173d-42bc-bca1-b82b6a1dc95f · outbound

This paper cites Dynaslam: Tracking, mapping, and inpainting in dynamic scenes,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Dynaslam: Tracking, mapping, and inpainting in dynamic scenes,

Reference 3

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raw_fallback, observed 2026-08-11T23:32:14.014228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.101886Z digest=sha256:dcda70dc1f8094f40140af5a708920326c5887558482bc5ab8b0133966c952c7

Observation 4041a1b1-148c-456a-9adc-e1c9bd03fdcc · outbound

This paper cites Ds- slam: A semantic visual slam towards dynamic environments,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Ds- slam: A semantic visual slam towards dynamic environments,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.995239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.107071Z digest=sha256:5811d8222d8fa1ff1e30398b965d9873e0344b26370b623ef91c5ef0c660b2a9

Observation 06b08896-bda0-4fb3-898f-510d254bac47 · outbound

This paper cites Mid-fusion: Octree-based object-level multi-instance dynamic slam,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Mid-fusion: Octree-based object-level multi-instance dynamic slam,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.975796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.113607Z digest=sha256:4649fca1b9a41cbd05c4ded893a393dcc19ac95fa237e5fc6fa67497e0d2db81

Observation fad1299a-b2be-404e-b5f4-639763bb3f7d · outbound

This paper cites Objects can move: 3d change detection by geometric transformation consistency,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Objects can move: 3d change detection by geometric transformation consistency,

Reference 6

Resolution
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raw_fallback, observed 2026-08-11T23:32:13.958781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.119009Z digest=sha256:00e7b84b0ca582a5195ec6dfd434a992db0691de23ae6d77455b9d794b4d86a0

Observation baa06743-5af7-432f-ba5e-fe04883a0139 · outbound

This paper cites Has Anything Changed? 3D Change Detection by 2D Segmentation Masks.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Has Anything Changed? 3D Change Detection by 2D Segmentation Masks

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.124596Z digest=sha256:ad3dc924f3b7ae0cb92f8a7a6e65559ec978f0e7b16876feed4bdf159444f47e

Observation dab6bfd8-b35d-474c-a6d2-8e3d65be6df2 · outbound

This paper cites Living scenes: Multi- object relocalization and reconstruction in changing 3d environments,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Living scenes: Multi- object relocalization and reconstruction in changing 3d environments,

Reference 8

Resolution
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raw_fallback, observed 2026-08-11T23:32:13.943434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.129936Z digest=sha256:994c26c708dbfd6c077fe5d66362bbfa12c5f57dde075d37553d1d710c6d4279

Observation c8204d9f-aa53-44eb-8d88-94009103d94c · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding ShapeNet: An Information-Rich 3D Model Repository

Reference 9

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no resolver link, observed 2026-08-11T23:32:13.135539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.135539Z digest=sha256:950ad655172f2b2e863fcded8295145d91ddd35c6ef0608810d2f2b1e86de8b0

Observation 95318ce9-b0e8-46f7-9690-f0cd3b655e68 · outbound

This paper cites Langsplat: 3d language gaussian splatting,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Langsplat: 3d language gaussian splatting,

Reference 10

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source=pdf_text observed=2026-08-11T23:32:13.141207Z digest=sha256:ccb77967e6971be9f302da80cfb6cc20c361675088249fae5df379493fc1aeec

Observation e0b0454d-e12b-4d38-b246-3c26f0c9e016 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding 3d gaussian splatting for real-time radiance field rendering

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.145646Z digest=sha256:539730c1a53eb7e2b8939bcbe99b5aeb8b57b7718fd9d16632c5aba55d834beb

Observation 765bf078-6c0e-4aeb-8ca6-43bfc85cbba4 · outbound

This paper cites AI2-THOR: An Interactive 3D Environment for Visual AI.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding AI2-THOR: An Interactive 3D Environment for Visual AI

Reference 12

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no resolver link, observed 2026-08-11T23:32:13.149398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.149398Z digest=sha256:e0aa15e6682b62af3caab8f2f5f33d7e8e67de13c686f38c0172fc755bf59047

Observation b4ef147f-f76b-4167-8068-9fff7a7537d2 · outbound

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

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Learning transferable visual models from natural language supervision,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.155028Z digest=sha256:e88999c5e15ae77cef793bf3695a95313d69d91c458ac6d39cb6acb4b00aa2e4

Observation 64a9368a-650a-450b-9338-8de814e76ee6 · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Open-vocabulary semantic segmentation with mask-adapted clip,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.905656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.161292Z digest=sha256:c2fed77f3b4df028bc0c4278a74c9aa0d8d95d39f3cf0bfbb5eb1dff5946a357

Observation 2964ff3b-b419-4e5b-8a7f-f98525aaa127 · outbound

This paper cites Scaling open-vocabulary image segmentation with image-level labels,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Scaling open-vocabulary image segmentation with image-level labels,

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.165243Z digest=sha256:91e209b758b8bb4cc06d3d1820e9b04644381f3791dfc7e4723f667891e002de

Observation 9ba93c6a-fcb1-44b8-bc81-34b3c4597bbe · outbound

This paper cites Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,

Reference 16

Resolution
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raw_fallback, observed 2026-08-11T23:32:13.872160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.169021Z digest=sha256:27581b893965f7bae3b7487850052432f40ee7c651fd711b5945cc0a2801a61b

Observation 439c5779-8b29-4af4-808e-e030dbfa5a60 · outbound

This paper cites Visual language maps for robot navigation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Visual language maps for robot navigation,

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.172919Z digest=sha256:938b57b66ea9d9d596e544ac53645a522586e972c62294cd20cffc767789cb6b

Observation 7b339340-4fee-4882-9d85-da4522d85908 · outbound

This paper cites Concept- graphs: Open-vocabulary 3d scene graphs for perception and planning,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Concept- graphs: Open-vocabulary 3d scene graphs for perception and planning,

Reference 18

Resolution
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source=pdf_text observed=2026-08-11T23:32:13.176757Z digest=sha256:1dd0a59d369453e23db2495b277155a5eebc9c1264f6a40bbef5992011c65e91

Observation c420878f-1e81-44f7-bffa-07e870912746 · outbound

This paper cites Audio visual language maps for robot navigation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Audio visual language maps for robot navigation,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.838996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.181350Z digest=sha256:471e35a7024be7dd9d02347bcf6ca3b381d8075b1be975ff32174dfbc1633cf3

Observation 5f718421-d151-4d68-9454-9178d5d56ab0 · outbound

This paper cites Hi- erarchical Open-V ocabulary 3D Scene Graphs for Language-Grounded Robot Navigation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Hi- erarchical Open-V ocabulary 3D Scene Graphs for Language-Grounded Robot Navigation,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.824551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.185580Z digest=sha256:18ba8909e98225fac7240fca8188ef0b78c9f7591f6aad192ec4be335db52a59

Observation 1809c5eb-8241-4806-872f-262354a83f35 · outbound

This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.190124Z digest=sha256:2f7d4ada36a7043ff2d4fa7cc479246eded11f9aa253b95a07c8c556be48a184

Observation 27c8e546-d2c4-4912-9776-e847671b14f6 · outbound

This paper cites Lerf: Language embedded radiance fields,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Lerf: Language embedded radiance fields,

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.198215Z digest=sha256:51d40d58e068999e1bc909ba30ca9a7305baae706efbfe856c9b59aad067f568

Observation ffbb8614-d555-41be-b760-3a9ac5c892d8 · outbound

This paper cites Openscene: 3d scene understanding with open vocabularies,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Openscene: 3d scene understanding with open vocabularies,

Reference 23

Resolution
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no resolver link, observed 2026-08-11T23:32:13.203121Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.203121Z digest=sha256:4e4c56f76eb34c25e404d3ef3589af120f64c7d5534f6ba7f909ddada1eeb61d

Observation e9d7eacb-eab9-4702-8d6e-b11e84d5a383 · outbound

This paper cites Conceptfusion: Open-set multimodal 3d mapping,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Conceptfusion: Open-set multimodal 3d mapping,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.786631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.207483Z digest=sha256:79419701e37733430a447e346e14cd1c362031e5ad7b45fefe99e12b878adfd0

Observation 35be9845-8a8a-401e-9e63-a95bde7f0300 · outbound

This paper cites OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.771773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.213484Z digest=sha256:2b53fcd0b37f298bd48ca91c5ae1d650715a3650588c8cb652dd069c1c534f02

Observation a559fa3c-4d48-4c84-82c1-4466433814ee · outbound

This paper cites Garfield: Group anything with radiance fields,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Garfield: Group anything with radiance fields,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.756850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.218672Z digest=sha256:9e898f07589a43d99c6022b2c8e3615305b21ff51f836bdfcc7566f0c96230c4

Observation 1eb93b9d-673a-4385-89d9-b9ef689370ba · outbound

This paper cites Fusion++: V olumetric object-level slam,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Fusion++: V olumetric object-level slam,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.224044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.224044Z digest=sha256:94aaf053d16aba594062b64f988b3c974e923221a5573bbcda8311624604656d

Observation 57a668ed-5bcb-497d-8841-4c8dcf87b078 · outbound

This paper cites Flowfusion: Dynamic dense rgb-d slam based on optical flow,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Flowfusion: Dynamic dense rgb-d slam based on optical flow,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.731802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.230270Z digest=sha256:44dd76b15b0a78669daaa80837d6076fba19e89417f18f564191d88ad30ed2f7

Observation 3df8035b-8b58-4d7b-885c-4d5ddc6b8f35 · outbound

This paper cites Dynamicfusion: Recon- struction and tracking of non-rigid scenes in real-time,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Dynamicfusion: Recon- struction and tracking of non-rigid scenes in real-time,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.238230Z digest=sha256:a59eb9034295f9ef6153443d5a91825d7c79ed17b7ca25171b0b7bcffd51965d

Observation a3a27249-7698-4e33-95df-305aed749121 · outbound

This paper cites Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis

Reference 30

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no resolver link, observed 2026-08-11T23:32:13.243246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.243246Z digest=sha256:697ba15516587179e513661db8ba50ee426f80c74999c71a1b9e691837029995

Observation 99faa44f-af0f-415f-84f8-bb2e6d464044 · outbound

This paper cites Phys- gaussian: Physics-integrated 3d gaussians for generative dynamics,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Phys- gaussian: Physics-integrated 3d gaussians for generative dynamics,

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.248309Z digest=sha256:264318cd99b8aa8d9026f1eb7d4cb340c6a919efd0646ffac80c5d51d4c34b75

Observation 30ac95d4-47d0-411c-836c-319fa030d368 · outbound

This paper cites Robust change detection based on neural descriptor fields,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Robust change detection based on neural descriptor fields,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.702193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.253625Z digest=sha256:b0b64fe8625cb996be75efff40da62000bbc5562b5cc384acb6b05b250e366d4

Observation cfb1d430-e2f6-4a68-a7e8-1adc6cb44f67 · outbound

This paper cites Indoor scene change captioning based on multimodality data,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Indoor scene change captioning based on multimodality data,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.688263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.258817Z digest=sha256:0ec8acbf21a052ef1e7893e14bd4d8d4e048accdd5d4284284f7011a6d9bd890

Observation ac1a302f-09cc-4f36-bdde-e710e62249bc · outbound

This paper cites 3d vsg: Long-term semantic scene change prediction through 3d variable scene graphs,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding 3d vsg: Long-term semantic scene change prediction through 3d variable scene graphs,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.673705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.263167Z digest=sha256:d767f7ad455b0b0fc4dff9fbbd1b36b604042f77d0792a2cf7e7bbdf43f0f3c8

Observation 3b5d5cd5-89d5-46ed-8c56-db09ad8b336f · outbound

This paper cites Khronos: A unified approach for spatio-temporal metric-semantic slam in dynamic envi- ronments,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Khronos: A unified approach for spatio-temporal metric-semantic slam in dynamic envi- ronments,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.656947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.267297Z digest=sha256:9aeab5faa055d9643d6bdd31d328ba09dba4b7e318e1a9dd18a3a03ade312acb

Observation 86aac150-5a4f-4280-935f-7571f66c5d2a · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Pointnet: Deep learning on point sets for 3d classification and segmentation,

Reference 36

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unresolved
no resolver link, observed 2026-08-11T23:32:13.271806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.271806Z digest=sha256:efddefc1072c4fec263ffd3adcafe97e44c5d8a4e62ade023215ebe37363dc8d

Observation 017a2e74-7a4f-4eac-b1d2-5900b581b3c7 · outbound

This paper cites Dynamic graph cnn for learning on point clouds,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Dynamic graph cnn for learning on point clouds,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.276592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.276592Z digest=sha256:7566f4519b9bc5779cc34c7a480c071732e081f1e4efa1933bed56f283663389

Observation 805449d7-21ae-427c-a8f8-b75971ffc70b · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape rep- resentation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Deepsdf: Learning continuous signed distance functions for shape rep- resentation,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.281329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.281329Z digest=sha256:2c2c7afdbd16ec2d150b9439273c38f0dd440f95225e106a76635441911b76ff

Observation 00e35557-44b7-4be1-bc62-9e8456937ac3 · outbound

This paper cites Learning implicit fields for generative shape modeling,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Learning implicit fields for generative shape modeling,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.616317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.285586Z digest=sha256:d0db69c347e2c7a4b9b72cdab514c26784fadc81159842e84bbbf3f165706e4b

Observation 9f396d5b-17b1-41d4-bd96-269a688417fb · outbound

This paper cites Coarse- to-fine point cloud registration with se (3)-equivariant representations,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Coarse- to-fine point cloud registration with se (3)-equivariant representations,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.600121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.290295Z digest=sha256:0daa72fdbd63d2eaa74fc919799168c6d2eacce2b4c3f1286d05a2301e99938a

Observation a805f033-bb08-4c43-9c22-e21667bf83c8 · outbound

This paper cites Neural descriptor fields: Se (3)-equivariant object representations for manipulation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Neural descriptor fields: Se (3)-equivariant object representations for manipulation,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.585060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.294483Z digest=sha256:39ed992e8f52d796beb66def31cec12347cb8def50157ffa9eb4b2261feaf8f0

Observation cc8d1dbe-e030-4d07-b69c-f329d434b359 · outbound

This paper cites Neuse: Neural se (3)-equivariant embedding for consistent spatial understanding with objects,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Neuse: Neural se (3)-equivariant embedding for consistent spatial understanding with objects,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.565279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.298642Z digest=sha256:90fe3921c74d1ede2339bd7044b4b550d7909beda6146507f84fcdf74fd2b85c

Observation e040f418-5466-4e8a-9444-d62b381760c6 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding A simple framework for contrastive learning of visual representations,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.302483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.302483Z digest=sha256:7cfd263e6e9a77f1d14a9d0ff61a3ec43617fe9dd2cdfc019bce694c7c206548

Observation 31892ba7-4f42-4f00-b6a1-b4aba30e6771 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.306948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.306948Z digest=sha256:0311f0bbb3f0583ff43383571c7fc3b8c86279649d05bb6fd2e7105f29576428

Observation 31df61c9-33d7-4071-8aa2-b9248b3a08e8 · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Improved deep metric learning with multi-class n-pair loss objective,

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.312140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.312140Z digest=sha256:3f1f132f354a9025e5f91b7c30528f63cea9f78f4543f1397e9b349997efaae3

Observation cfc74011-9cce-473f-a1d9-cfd2579ac7e7 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding DINOv2: Learning Robust Visual Features without Supervision

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.316162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.316162Z digest=sha256:5dd493d775a5b06056b0c23566fe55c303295a43ca38d41f0c0d0055bce546ad

Observation 82d38ed5-c79e-4e1c-b881-c8682508ee9c · outbound

This paper cites Language-driven semantic segmentation,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Language-driven semantic segmentation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.517764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.320757Z digest=sha256:0aef2e9d1c8491da66d0ca34206e31e1d456ea1c277d6b09c81c15e8bc5ef7c0

Observation a495c29a-5fbb-479c-a495-cd86c22a580d · outbound

This paper cites Density-based spatial clustering of applications with noise,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Density-based spatial clustering of applications with noise,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:32:13.502212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T23:32:13.325424Z digest=sha256:4d9a5a188f0e9e4005c61b75ecac64a0cd92323fe363e9fc0dacbed7c41c6cac

Observation 883dd30c-8aa9-4974-8b2d-2f21b063900e · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding SAM 2: Segment Anything in Images and Videos

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.329892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.329892Z digest=sha256:6dbff76c9016b2b6a01a1ae510719ea7deb1d5ccf7171b5ded307ad5a7843cb3

Observation 8a4c5cc3-b724-4fda-a323-f41d9b9fe4c8 · outbound

This paper cites Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras,.

BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras,

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T23:32:13.335331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:32:13.335331Z digest=sha256:88dc85e73c6e2ec3f285fbe2dcaf480bc345b222d35ee70b7c6bb8db5fccb547

Pith citing papers

No inbound Pith citation observations are available.