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Paper Citation Record · LEDGER

ChartAdapter: Large Vision-Language Model for Chart Summarization

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2412.20715.

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

pith.paper-citation-record.v1
2412.20715 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:15:33.662653Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T20:07:23.153064Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy26
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation b0a21cd6-c730-44fd-910b-d98eaecd01a7 · outbound

This paper cites Tinychart: Efficient chart understanding with program-of- thoughts learning and visual token merging,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Tinychart: Efficient chart understanding with program-of- thoughts learning and visual token merging,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.261945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.516296Z digest=sha256:80885ae1b1a84ff7ace04cc584b185eeb8c4dc9f1c0b2d08d9c22ceac9909b4c

Observation b04db5ba-ecfc-400c-954f-c5a402997c55 · outbound

This paper cites Fashionregen: Llm- empowered fashion report generation,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Fashionregen: Llm- empowered fashion report generation,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.247905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.521467Z digest=sha256:6f689cc8252100b453faf2c3a009fe3bdfb170569809a1b913569affd6c4eaab

Observation f96ce1b1-7449-4eca-b277-0b7d340a5f56 · outbound

This paper cites A Survey of Large Language Models.

ChartAdapter: Large Vision-Language Model for Chart Summarization A Survey of Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.525949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.525949Z digest=sha256:1590f0a2d032386a6c2bd84b76dcfeb2d99f4d330c48b70560dabab02dad5599

Observation 9d275c63-6c50-40ea-95be-20575d511c52 · outbound

This paper cites A survey on RAG meeting llms: Towards retrieval-augmented large language models,.

ChartAdapter: Large Vision-Language Model for Chart Summarization A survey on RAG meeting llms: Towards retrieval-augmented large language models,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.233905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.530755Z digest=sha256:2236f49ed1e79f4d871a1569de1bc4fd27e8281be35e1d924e0a97aa985ccd28

Observation bd9c8331-64c2-4a60-a8e0-4a3bcd6aa415 · outbound

This paper cites Graph Machine Learning in the Era of Large Language Models (LLMs).

ChartAdapter: Large Vision-Language Model for Chart Summarization Graph Machine Learning in the Era of Large Language Models (LLMs)

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.535355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.535355Z digest=sha256:ee09a50d2d0f4175ce1a19a29d98dd34dffe9f87d5bc82d867833b5e28ce1bc0

Observation 76947c8d-d33e-48bd-a903-a447601bb9a4 · outbound

This paper cites Chartstamp: Robust chart embedding for real-world applications,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Chartstamp: Robust chart embedding for real-world applications,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.220094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.540430Z digest=sha256:11d4a369da3be07e5dc81556a7935f22c788399e3b5f65dca8fef2b133e94f20

Observation 3492a933-1a0d-4528-abcf-30c85a6a4f98 · outbound

This paper cites Deplot: One-shot visual language reasoning by plot-to-table translation,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Deplot: One-shot visual language reasoning by plot-to-table translation,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.206682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.545217Z digest=sha256:35e67be551325d6745f833a99f6ef491da77fc4ba8c84a8d57ef82ee0ba4e28c

Observation b12f0e7e-f074-42b9-973a-8250227c8d0c · outbound

This paper cites Chartqa: A benchmark for question answering about charts with visual and logical reasoning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Chartqa: A benchmark for question answering about charts with visual and logical reasoning,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.192860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.549435Z digest=sha256:858a8f5b551cc29e975f1961bd6e4ca985a352e55338532d1f715e064c7fe79f

Observation cd664673-f208-4daa-a213-bc3687dbbe00 · outbound

This paper cites An architecture for data-to-text systems,.

ChartAdapter: Large Vision-Language Model for Chart Summarization An architecture for data-to-text systems,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.178315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.553634Z digest=sha256:34e78cd6e39c328a18f2a9435bb9ad519eb1bb12cb65a78f7ea9bcfe9fcf6c0c

Observation 28d3dd3f-43a8-4541-9634-251540db10d2 · outbound

This paper cites Chart-to-text: A large-scale benchmark for chart summarization,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Chart-to-text: A large-scale benchmark for chart summarization,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.163499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.557774Z digest=sha256:a52783ae102f15344c66bc71d0362e621a4629facc808c1bbb20b84e70dd383d

Observation e9d5a6c5-1852-4627-a095-2363099ced80 · outbound

This paper cites Chartsumm: A comprehensive benchmark for au- tomatic chart summarization of long and short summaries,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Chartsumm: A comprehensive benchmark for au- tomatic chart summarization of long and short summaries,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.148834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.562995Z digest=sha256:9cb2fc3fe65b2cb776390c2bf1724b887844be8638b8731d2d9cb81b5e1c956f

Observation 44b2426f-95f0-4802-9c29-db4b2aec3811 · outbound

This paper cites Compositional semantic parsing on semi- structured tables,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Compositional semantic parsing on semi- structured tables,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.133511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.567984Z digest=sha256:671a582c6b1ea76d8bf5350a174eccaaf6c31de31b2725fbf3d60b7d71d5fdb4

Observation f5d4e6e1-ef9f-44aa-8365-3b07d2442554 · outbound

This paper cites ChartLlama: A Multimodal LLM for Chart Understanding and Generation.

ChartAdapter: Large Vision-Language Model for Chart Summarization ChartLlama: A Multimodal LLM for Chart Understanding and Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.573356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.573356Z digest=sha256:ce51996ed5eb9361683ecde333546ed897cabf986c0fde42d48414fd32dc56f2

Observation 79323de9-60ec-43f7-9786-d342d6162e3d · outbound

This paper cites Matcha: Enhancing visual language pretraining with math reasoning and chart derendering,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Matcha: Enhancing visual language pretraining with math reasoning and chart derendering,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.119921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.577865Z digest=sha256:5c5cd6ba308c11e81c9baf73da66e9b606701db7f31371f39bb322d3bd199e66

Observation a941dee7-d6c9-42ee-ad14-1fcdd9e712c1 · outbound

This paper cites Chartinstruct: Instruction tuning for chart comprehension and reason- ing,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Chartinstruct: Instruction tuning for chart comprehension and reason- ing,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.105673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.582120Z digest=sha256:ea0c1655620e6d99fe1bbddacc3aa9dc4d4517f18b3d8d56a6a538f5e94c41d7

Observation 80726b40-7eb7-4c3c-9ebe-162b0f720089 · outbound

This paper cites Unichart: A universal vision-language pretrained model for chart comprehension and reasoning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Unichart: A universal vision-language pretrained model for chart comprehension and reasoning,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.090979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.586105Z digest=sha256:aec7d296d483c1b33ac528b653227a2727cc964e1282e3a532d5742a9a53d8b6

Observation 5ee837e2-95af-4a4c-9b2b-f9c9df226ee7 · outbound

This paper cites Opencqa: Open-ended question answering with charts,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Opencqa: Open-ended question answering with charts,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.077770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.590599Z digest=sha256:a73f462cc121ab3437bbc11a643f095cedfdd3233e1e39a0addfb0347641cee3

Observation 51341acc-b7a9-4e0d-9c67-4c2ee37b883d · outbound

This paper cites Visual instruction tuning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Visual instruction tuning,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.594551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.594551Z digest=sha256:2fa52c0d6ed99b3953a66ddaf7080dc4d262c15ecbabbb539bb6061f34402c3e

Observation 23f17462-1910-4113-ab27-17c2b15b696e · outbound

This paper cites Gallerygpt: Analyzing paintings with large multimodal models,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Gallerygpt: Analyzing paintings with large multimodal models,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.054837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.598688Z digest=sha256:56088803c46e4fe10d5b890659b46c8f6da3ea7f1cfe837ad7a326a50f435c3b

Observation 41f0af6c-79f3-4fbd-9e29-adb051051b95 · outbound

This paper cites Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.041851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.602850Z digest=sha256:751c555501191edc5ed874b0b02894068570f2b25ab3c9b7104e195c6eac0cf5

Observation c64ca03d-0a87-4d15-a47c-9978d60ce5ff · outbound

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

ChartAdapter: Large Vision-Language Model for Chart Summarization Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.607132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.607132Z digest=sha256:ddca03d35a34b2ff87ac13b2b160798b5fa532b6da99f9efc178a606dc13b026

Observation 0c8ec933-7cbf-4db2-a40a-c51d7c46982c · outbound

This paper cites MM1: methods, analysis and insights from multimodal LLM pre-training,.

ChartAdapter: Large Vision-Language Model for Chart Summarization MM1: methods, analysis and insights from multimodal LLM pre-training,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.028919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.611304Z digest=sha256:ae4316a81fa5d131d61c4744742f7dcc1a102e29de7597f2a2b04b4da2463dd9

Observation b8f12166-8b0b-4567-8223-bc3e197d68a5 · outbound

This paper cites xgen-mm (BLIP-3): A family of open large multimodal models,.

ChartAdapter: Large Vision-Language Model for Chart Summarization xgen-mm (BLIP-3): A family of open large multimodal models,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.615504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.615504Z digest=sha256:bd666383b1c1498fbae1b3d17ae7bcbc968c461bd0b7ee6bfa26eee236246470

Observation c6c1ab4e-8ed5-4439-828c-8d260fc63d0e · outbound

This paper cites Align and retrieve: Composition and decomposition learning in image retrieval with text feedback,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Align and retrieve: Composition and decomposition learning in image retrieval with text feedback,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.015556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.619477Z digest=sha256:3641b3939d2242395288e59dc91f49e8c32534c7e5bd61a019cfe36dbbddbe8d

Observation 94465874-ef51-4ed6-99e6-d62c51a45cf9 · outbound

This paper cites Improved baselines with visual instruction tuning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Improved baselines with visual instruction tuning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:34.002279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.623650Z digest=sha256:482b2696a061391889d997da89704e597d6c5c14425a91219fc18f4d3772519f

Observation ec625e38-0c77-41b2-b772-9f44a570294a · outbound

This paper cites Leveraging weak cross-modal guidance for coherence modelling via iterative learning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Leveraging weak cross-modal guidance for coherence modelling via iterative learning,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.989323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.628098Z digest=sha256:5e68a3cd17edbd3754178a0473ad165aad5f6ae7ba216c67e1a3249a22fddf79

Observation 389292e5-05b5-4b3e-8d7f-209c52b77e95 · outbound

This paper cites BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large lan- guage models,.

ChartAdapter: Large Vision-Language Model for Chart Summarization BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large lan- guage models,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.974603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.632782Z digest=sha256:9c912216a0eef2ad4b180ea08eceef2b505f416716dc6b996e72fa3a984cc462

Observation 74150ee4-b100-47af-96d2-784da09e88ed · outbound

This paper cites Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.957522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.636889Z digest=sha256:f591611f3db60f740cb602608b2b1241e0a35c3af7a2307b4b36b9a43c3c4f3a

Observation 5d6c5f4d-0203-439c-9142-07e69e183870 · outbound

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

ChartAdapter: Large Vision-Language Model for Chart Summarization Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.641261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.641261Z digest=sha256:e2e972948296d701f353659f8dd98adf3f0b32437781fdbcbde8b72735393e0f

Observation 8c72d27b-245d-48b6-b389-ee4c4a24ad4d · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Learning transferable visual models from natural language supervi- sion,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.943397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.645582Z digest=sha256:4e62543bdc86678f5ce50bb09afd6b14052c379ee11858b7d095d21d8a2b3655

Observation eb324e17-0ce4-4438-9dbf-75e8a827f87e · outbound

This paper cites Vistext: A benchmark for semantically rich chart captioning,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Vistext: A benchmark for semantically rich chart captioning,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.928725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.649821Z digest=sha256:4844be015a5068259f79655d5d6bdd34b928a5c82d39147f99b607cb9b762e64

Observation 092731cb-3580-455e-922a-784201b29aa0 · outbound

This paper cites Pix2struct: Screenshot parsing as pretraining for visual language understanding,.

ChartAdapter: Large Vision-Language Model for Chart Summarization Pix2struct: Screenshot parsing as pretraining for visual language understanding,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.914798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T23:15:33.653905Z digest=sha256:8c4d6fe73b3795c422b8d43cd834d558397e08c6958647de23c2d30a773411a7

Observation 9a126658-53f2-42e5-82a8-bbc2013f5463 · outbound

This paper cites ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning.

ChartAdapter: Large Vision-Language Model for Chart Summarization ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T23:15:33.657872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:15:33.657872Z digest=sha256:2168b51338f25e2ee038035896ef4101b2cb471e6d3af37ab7877d2644dfe6ba

Observation 90bf2a57-fcb5-4fb9-8a88-ed1f6ef34207 · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding,.

ChartAdapter: Large Vision-Language Model for Chart Summarization BERT: pre-training of deep bidirectional transformers for language understanding,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:15:33.900319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

Observation b75aefce-c075-47a7-8c79-d7b2ec02ce4b · inbound

CharTool: Tool-Integrated Visual Reasoning for Chart Understanding cites this paper.

CharTool: Tool-Integrated Visual Reasoning for Chart Understanding ChartAdapter: Large Vision-Language Model for Chart Summarization

Reference 54

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arxiv_id, observed 2026-05-13T20:08:12.311763Z

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source=arxiv_source observed=2026-05-13T20:07:23.153064Z digest=sha256:2d0d9ad4a5c76e6ca362d271f9940891ba2ce462e9a833c8667bc65990003ccd