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Paper Citation Record · LEDGER

CLGRPO: Reasoning Ability Enhancement for Small VLMs

As of 18 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.18048.

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

pith.paper-citation-record.v1
2506.18048 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:46.110145Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

32 of 32 outbound references displayed

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  • verified fuzzy11
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 888e2e60-e219-475c-aaa1-b528e274bd99 · outbound

This paper cites Qwen2.5-VL Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen2.5-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-06T23:27:45.974336Z digest=sha256:7a8663a82bd3eb9a27b1a5ba4a3bd6dddbbf7d8d9bf963c40a3cf94a056bbee3

Observation a1cba944-ef9a-4c3a-a1c9-8028410c4f07 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 2

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source=pdf_text observed=2026-08-06T23:27:45.979535Z digest=sha256:367e5f4e98ae9d7c5ec7bcc70007c42201f3853e21b084a9f5546ea31c7583f0

Observation f2dd7f1e-2c03-4ef2-a355-09707d2a1102 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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source=pdf_text observed=2026-08-06T23:27:45.983521Z digest=sha256:c5a102ba3c67e00006eee7c4e4660473acd3d7a151aee56471260040022a145c

Observation cba8af1b-81fd-4ced-9f49-ae5ffed51561 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

CLGRPO: Reasoning Ability Enhancement for Small VLMs InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 4

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source=pdf_text observed=2026-08-06T23:27:45.989262Z digest=sha256:540ad15408002aaee0bc5eb57068b3914225fecf04afad343eda8787361c8357

Observation 90a389ff-562d-4d1b-91ea-8c4c79769133 · outbound

This paper cites Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance,

Reference 5

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raw_fallback, observed 2026-08-06T23:27:46.470968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:45.994230Z digest=sha256:d844359268d32de845d3304c66aa16a590b08e198fdca42efd19ce9dc4a90515

Observation 6d3a24bb-b916-4c08-ab3f-7e6750106c24 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks,

Reference 6

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source=pdf_text observed=2026-08-06T23:27:45.999090Z digest=sha256:5c6ffade88e8d5d5f837b3056fd140611cf0bea23b03e31e72f8ac51dcce8243

Observation 50e3175e-3585-44a1-98de-9522d7dd512d · outbound

This paper cites DeepSeek-V3 Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-V3 Technical Report

Reference 7

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source=pdf_text observed=2026-08-06T23:27:46.003577Z digest=sha256:0f14357ee889dda152b89ed0e65f94df4c923647cf240de88259f3df4d36ab9f

Observation e0358bca-d770-4939-a258-2b3bc14b349a · outbound

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

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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source=pdf_text observed=2026-08-06T23:27:46.007744Z digest=sha256:68feb2059d80c273356253f522ee08ed130d1922cb70c0ad07efa7e3c94009c0

Observation 42dd53b1-eaeb-4e1d-b910-9944b3080290 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 9

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source=pdf_text observed=2026-08-06T23:27:46.011940Z digest=sha256:15d99a7295b1bc048f5c1b85c873e6ab42ff4de13f1e0a6ef033a9bada571e5d

Observation d0fb5213-c107-4e06-92fa-b3a58308bd0f · outbound

This paper cites Deepseek-vl: Towards real-world vision-language understanding,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Deepseek-vl: Towards real-world vision-language understanding,

Reference 10

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raw_fallback, observed 2026-08-06T23:27:46.453110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.016387Z digest=sha256:c095fabae6e10245b1241a388543c4c71628d96cff4e16f0242c37ad73d4ebac

Observation 5f0c31ce-2ba5-405e-8461-e7f9f6165736 · outbound

This paper cites Fastvlm: Efficient vision encoding for vision language models,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Fastvlm: Efficient vision encoding for vision language models,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.019994Z digest=sha256:2c76f17b9b20bb4148ae1738fdae2618bf2cfba8bc92d493a295b86330f1f45a

Observation ed8b03db-ccc0-4a2b-9581-1552711e4495 · outbound

This paper cites Emoset: A large-scale visual emotion dataset with rich attributes,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Emoset: A large-scale visual emotion dataset with rich attributes,

Reference 12

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raw_fallback, observed 2026-08-06T23:27:46.431841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.023951Z digest=sha256:ca5705bf884b7d7cda11fc548b8abf30cd9ddd0433243f11120554b370230537

Observation ce9df91b-8665-4023-9d7b-f4c7c11313ee · outbound

This paper cites How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites,

Reference 13

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source=pdf_text observed=2026-08-06T23:27:46.027925Z digest=sha256:d7ebaf922e17b37b45fe455c8f8036f8e3bb50e2ca4cd5557fd5381e1a728524

Observation 206915a0-b4c3-415f-a14c-faa7b1913a53 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 14

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source=pdf_text observed=2026-08-06T23:27:46.031851Z digest=sha256:3080cfdda1a6c41f546a84e3adfb71a016b4c3a92c03487c42b1fc6748166ccd

Observation 5ed44390-3232-42df-8999-d4f09e64286c · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 15

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source=pdf_text observed=2026-08-06T23:27:46.035574Z digest=sha256:4101a92f57b54b6c71780043b563c92fba6cf55e944d437b3395ce3487aacffd

Observation e1df0161-d7f3-42f0-8aef-8431d30554c3 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

CLGRPO: Reasoning Ability Enhancement for Small VLMs MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 16

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source=pdf_text observed=2026-08-06T23:27:46.040045Z digest=sha256:ab28e419830c0d99007a9c8f220249b5146aaad7125f4255f2811a52d7c852e6

Observation 89775a5f-8141-4c5f-9d31-b8158f2da8b5 · outbound

This paper cites Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization

Reference 17

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source=pdf_text observed=2026-08-06T23:27:46.044306Z digest=sha256:4945380d0b028711c229518761dd844b83a167aa51e74b288c92cdad430dd58f

Observation c8760376-d25b-4280-92e6-05e754f0d73a · outbound

This paper cites Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput

Reference 18

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source=pdf_text observed=2026-08-06T23:27:46.048132Z digest=sha256:ec050c1c6ead1ec4fe7d38127e5ab2657be2fccf33b5229c3eca730b2bc0df4c

Observation c480aeb5-07ba-42a7-8fbf-2accc3867fe6 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct preference optimization: Your language model is secretly a reward model,

Reference 20

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raw_fallback, observed 2026-08-06T23:27:46.414377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.055921Z digest=sha256:8460a4c676df0c43a4c865a791efaf70c193e166f7e33c05b0f300d42d00b296

Observation d207f646-328b-46ae-86d1-f2c88e1be30d · outbound

This paper cites Bluelm: An open multilingual 7b language model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Bluelm: An open multilingual 7b language model,

Reference 21

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raw_fallback, observed 2026-08-06T23:27:46.401648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.065185Z digest=sha256:a196cd7ab2ddece14b5bc148dc912cf12b1e9d67561d9c80ba6adfcd0bd76fe2

Observation ceb4a625-f154-4dfd-a0d3-1f6ddc62b22b · outbound

This paper cites Qwen3 Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen3 Technical Report

Reference 22

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source=pdf_text observed=2026-08-06T23:27:46.069055Z digest=sha256:96c4b7de6759e72c79de8caaec9512dfa505744d4901b561d54ccf4298531a1f

Observation de30002b-577a-4f35-9999-6e7832abf485 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 23

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source=pdf_text observed=2026-08-06T23:27:46.073417Z digest=sha256:405f81e2400b3c41d047e8601134158d7e2f547b91b32c8a9dfbdb5bad9562ea

Observation 3b9f84a9-5d91-40d6-9fce-e92fbd59d6e5 · outbound

This paper cites Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,

Reference 24

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.077559Z digest=sha256:4a415a533afc9de38c473dfa14b8b0f3256bce347f4c1cf263923f83111c3382

Observation 9bcb828f-6da3-46a2-ba53-51a42189d87b · outbound

This paper cites Cot-vla: Visual chain-of- thought reasoning for vision-language-action models,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Cot-vla: Visual chain-of- thought reasoning for vision-language-action models,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.082144Z digest=sha256:1cfc393f0dbf74aedee6cd1291739fd1ee161fe700c66f15bbb393304edffe75

Observation ee782dab-a378-4cef-afb2-e68922e5d2a0 · outbound

This paper cites Proximal Policy Optimization Algorithms.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Proximal Policy Optimization Algorithms

Reference 26

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source=pdf_text observed=2026-08-06T23:27:46.086111Z digest=sha256:fa77bc7c3b3dacbb15ce2e6b0815af7af3e413722970f87c5f5483c39b51c8f6

Observation d977a308-3fa7-47c9-a607-864a0119acc8 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct preference optimization: Your language model is secretly a reward model,

Reference 27

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raw_fallback, observed 2026-08-06T23:27:46.368226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.090218Z digest=sha256:5fe1525dc080189d5d54093a5933875bba4a2d929b68d533c79ea3d00bceda91

Observation d4c51025-8c1d-4790-a00e-684a8a9963f4 · outbound

This paper cites Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms

Reference 28

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source=pdf_text observed=2026-08-06T23:27:46.094169Z digest=sha256:a5cbf6a96d4c66827d8e671b283f124cada3627de55357e66f247f583de85bfe

Observation c14be14c-f2bb-49ec-8019-2b136d1f5c00 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Understanding R1-Zero-Like Training: A Critical Perspective

Reference 29

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source=pdf_text observed=2026-08-06T23:27:46.098401Z digest=sha256:008d74af1f99b4bd4df06454deb40fe09a608c9214ea0f2d672aa6137818560d

Observation 3e0302b2-4c90-4d32-b153-02826c9f8c20 · outbound

This paper cites u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model.

CLGRPO: Reasoning Ability Enhancement for Small VLMs u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model

Reference 30

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source=pdf_text observed=2026-08-06T23:27:46.102560Z digest=sha256:492797a369d5d3cd499bf9d1e63330fa95e2f97ef060a156a94cf157dead0516

Observation 6fe2d866-1107-4922-acda-7c305a133f15 · outbound

This paper cites Reproducibility companion paper: u-llava: Unifying multi-modal tasks via large language model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Reproducibility companion paper: u-llava: Unifying multi-modal tasks via large language model,

Reference 31

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raw_fallback, observed 2026-08-06T23:27:46.357321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.106556Z digest=sha256:e646af6cca9fa8b5f1480adb64432aa62640e894ced864ac4e3429300d57d088

Observation 83592d12-7e03-4866-aeeb-60cdca07b7c4 · outbound

This paper cites Overcoming heterogeneous data in federated medical vision-language pre-training: A triple-embedding model selector approach,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Overcoming heterogeneous data in federated medical vision-language pre-training: A triple-embedding model selector approach,

Reference 32

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raw_fallback, observed 2026-08-06T23:27:46.344292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:27:46.110145Z digest=sha256:534ad1c410b1b5dee1f98b98f027ebcefe3023a524054038d7f4e3d1f32870bf

Observation cdb15741-233e-411b-970c-9479855144e2 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 2023

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:46.060328Z digest=sha256:b34472ddb8d8bd6b9f63fefaf6fd1e6eefbeb22611356709458a35e09962c5df

Pith citing papers

No inbound Pith citation observations are available.