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Paper Citation Record · LEDGER

Open-Det: An Efficient Learning Framework for Open-Ended Detection

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 3 inbound Pith citation observations for arXiv:2505.20639.

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

pith.paper-citation-record.v1
2505.20639 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:56:43.126975Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:33:55.317107Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T11:01:30.290086Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved10
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7ca85e9-faba-4228-8e9c-fa2a67255f45 · outbound

This paper cites GPT-4 Technical Report.

Open-Det: An Efficient Learning Framework for Open-Ended Detection GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.089096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.089096Z digest=sha256:d2230b4a36dc7f27bc3dad984ade206ec5c91ad6a1dce3cf3df96819e47ffd3d

Observation cf1c2349-0ebb-48f6-ad58-d1a85a144ad9 · outbound

This paper cites Decoupled Weight Decay Regularization.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Decoupled Weight Decay Regularization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.541246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.541246Z digest=sha256:3b7e09569a67a4767d5704efe26471b805c3d67d0996d300d0ca6c8fa38da37e

Observation 8a958259-d2bf-4e16-8ea3-e6785f8d75d7 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.609051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.609051Z digest=sha256:66d720d8469a62259d431f862fba21d34ed60e7a85363ca0980101455910a68c

Observation f3081a19-db8c-45de-9959-ee15f5393244 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.914319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.914319Z digest=sha256:cee95af52fc7b79ac92601e9ebb651243d35f27e76f7f276c225ee38f8d3517e

Observation f40d7f3d-1e44-4077-8170-3b3d1562d655 · outbound

This paper cites For each object query, the corresponding word in the text encoder is treated as a positive sample, while all other words in the same mini-batch are treated as negative samples.

Open-Det: An Efficient Learning Framework for Open-Ended Detection For each object query, the corresponding word in the text encoder is treated as a positive sample, while all other words in the same mini-batch are treated as negative samples

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:56:43.893211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T13:56:42.997319Z digest=sha256:774f7ba345f63f135a736678412b22a1c494d0c0c1daeb912e3db094df44e2c2

Observation 984a747d-158e-4333-aa60-dc6be130c970 · outbound

This paper cites soft loss.

Open-Det: An Efficient Learning Framework for Open-Ended Detection soft loss

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:56:43.719182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T13:56:43.062804Z digest=sha256:686ba03dd03280c9a73d2d0d1a720470d3568cb70a1cbe96de28b26a1cfc4c48

Observation d484648e-cecf-453f-a6b8-53944bbc617b · outbound

This paper cites As presented in Table 6, Open-Det achieves higher performance with only 31 training epochs, which is 20.8% of the epochs required by GenerateU ( 149 training epochs).

Open-Det: An Efficient Learning Framework for Open-Ended Detection As presented in Table 6, Open-Det achieves higher performance with only 31 training epochs, which is 20.8% of the epochs required by GenerateU ( 149 training epochs)

Reference 13

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T13:56:43.515022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T13:56:43.126975Z digest=sha256:46c32552e293d0a73c0f23db4b0230d1836c6954691adb74f7230cc48c61473d

Observation 840a9289-0d25-4d59-805c-0982b19137c9 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.448178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.448178Z digest=sha256:ea03a09860111c1f4ae51e65a3ca621d8116f8938cbeb365f16ee82f472cc0fd

Observation c3c48e0f-80b5-43b7-9b23-c7ea3b9f8c56 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.708973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.708973Z digest=sha256:1fe5b053c6425c617593e7c5f777918ee4db725ef8f67f54fed19a2d95f9909b

Observation 5104f42d-3c50-41ba-92f3-22106094dfc4 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Open-Det: An Efficient Learning Framework for Open-Ended Detection DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2021

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unresolved
no resolver link, observed 2026-08-07T13:56:42.154316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.154316Z digest=sha256:e2140b0f53d61100a670de9aba47768c4995bdcacc7fff14af5a23d66994b74e

Observation ab3d7436-9a67-44f6-8882-5046cfbd16cf · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

Open-Det: An Efficient Learning Framework for Open-Ended Detection DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.817022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.817022Z digest=sha256:56a1565e11c73ba88c3dbb493f67367680410b509ae0b0e8eb1a7965a2e07127

Observation 284b4517-feb3-4300-a177-fff87a09adce · outbound

This paper cites LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors.

Open-Det: An Efficient Learning Framework for Open-Ended Detection LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T13:56:42.274217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:56:42.274217Z digest=sha256:2aa80fddc518697c9401bb42fb079303040072ef7ba6b17156afe61db3d06d62

Observation afb07721-5c22-42b9-831d-6d47b5e7d1cc · outbound

This paper cites an unresolved cited work.

Open-Det: An Efficient Learning Framework for Open-Ended Detection Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:56:44.126344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T13:56:42.360085Z digest=sha256:76228c23256a47c7f6f0e55f6ad38428f48dcf4054eba62d15b621ca7bb99138

Pith citing papers

Observation 3351a498-1d4b-4354-b50e-77e6b6e66fa4 · inbound

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection cites this paper.

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection Open-Det: An Efficient Learning Framework for Open-Ended Detection

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-12T11:01:30.292734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-08T01:24:56.236650Z digest=sha256:3e70241a64996efd31f94b411a4377ebe90a21ee99e632c3a62bcf6800bd1df1

Observation 00554a0f-cb7b-4153-a1c7-47ea7b1783ed · inbound

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection cites this paper.

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection Open-Det: An Efficient Learning Framework for Open-Ended Detection

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:00:35.789099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-08T19:14:12.092478Z digest=sha256:33a5f4a0ce17694e64dbaac664a727c0370002882ad6bc605b9fe0e0284a5d48

Observation b0eb29ed-4ccb-4a67-9db8-4589382e36af · inbound

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection cites this paper.

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection Open-Det: An Efficient Learning Framework for Open-Ended Detection

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:51:48.469332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T01:33:55.317107Z digest=sha256:72dca68f056fa4e7099d7d90ccccfbd66c80ed761c0f686706561e519f555b71