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Paper Citation Record · LEDGER

LLaVA-c: Continual Improved Visual Instruction Tuning

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 9 inbound Pith citation observations for arXiv:2506.08666.

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

pith.paper-citation-record.v1
2506.08666 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:10:48.568952Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:25.878281Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:27:36.596565Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 918910c0-bb35-481a-a65a-b4783dcc3d2d · outbound

This paper cites Improved baselines with visual instruction tuning.

LLaVA-c: Continual Improved Visual Instruction Tuning Improved baselines with visual instruction tuning

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.387226Z digest=sha256:e21c55059a869ae30720d10a0adfcc3cc66186ce868832e8c8ac5c7cecd1779e

Observation 6650d064-5931-454f-958f-4d22c28aa3b5 · outbound

This paper cites Language models are few-shot learners.

LLaVA-c: Continual Improved Visual Instruction Tuning Language models are few-shot learners

Reference 2

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no resolver link, observed 2026-08-07T05:10:48.392876Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.392876Z digest=sha256:a7b7b589542abe9779375d71446fa5fd83de327fb6a4aa40161d32a589c05323

Observation fbf4840d-5202-40aa-806d-0e12ac51946b · outbound

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

LLaVA-c: Continual Improved Visual Instruction Tuning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 3

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no resolver link, observed 2026-08-07T05:10:48.397985Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.397985Z digest=sha256:5ed640883659f2cbeaf64213e3a4d8c2a9235fb124250caf6f90ad9dbae1bc9a

Observation 8dbeaec0-ea49-4770-9cb7-b6310d2ea7ba · outbound

This paper cites Visual instruction tuning.

LLaVA-c: Continual Improved Visual Instruction Tuning Visual instruction tuning

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.403574Z digest=sha256:6651328226b07c4f950fb5616f8642b5a96749a47a8ac39b690095641425f9d1

Observation 94a62543-d669-474c-b5e0-fc755d54274f · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

LLaVA-c: Continual Improved Visual Instruction Tuning Learning Transferable Visual Models From Natural Language Supervision

Reference 5

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unresolved
no resolver link, observed 2026-08-07T05:10:48.408822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.408822Z digest=sha256:3cf96b627bf76b10c9b6f90beceb671662938edad86491a7ac33d77ddbc24532

Observation 94031e9e-68a1-44ac-b7c7-263ca7fde382 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.Proceedings of the National Academy of Sciences, 114(13):3521–3526, 2017.

LLaVA-c: Continual Improved Visual Instruction Tuning Overcoming catastrophic forgetting in neural networks.Proceedings of the National Academy of Sciences, 114(13):3521–3526, 2017

Reference 6

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no resolver link, observed 2026-08-07T05:10:48.414095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.414095Z digest=sha256:c161d26aeed90e598392a4fb1a1dfd2a76035ec3e68c17c1a821df27ed296474

Observation c157bcf3-e1d7-492c-a561-4f5fd9e61325 · outbound

This paper cites CoIN: A benchmark of continual instruction tuning for multimodel large language models.

LLaVA-c: Continual Improved Visual Instruction Tuning CoIN: A benchmark of continual instruction tuning for multimodel large language models

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.169605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.419386Z digest=sha256:10c823ef7f00c492b93b39e2ee029df17dbe38e444c49172b03d4df41e5f9024

Observation 98f92714-9f6e-473d-bdbb-0bc793e218a2 · outbound

This paper cites Orthogonal subspace learning for language model continual learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Orthogonal subspace learning for language model continual learning

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.424011Z digest=sha256:90a2fd4ba910e5453156bef1a90c8e37dc1bfbecd051dc2a0087ec8db8ce1dc2

Observation c3f9f4d7-c052-44d1-bb6b-6cb51cb02106 · outbound

This paper cites ModalPrompt: Towards Efficient Multimodal Continual Instruction Tuning with Dual-Modality Guided Prompt.

LLaVA-c: Continual Improved Visual Instruction Tuning ModalPrompt: Towards Efficient Multimodal Continual Instruction Tuning with Dual-Modality Guided Prompt

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.428757Z digest=sha256:86db84862e917c27d465d831076d44c10153c472b577f116cbe832357762522b

Observation 84a8c427-0c20-4055-8ed9-70c4581620fb · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

LLaVA-c: Continual Improved Visual Instruction Tuning PaLM: Scaling Language Modeling with Pathways

Reference 10

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no resolver link, observed 2026-08-07T05:10:48.433679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.433679Z digest=sha256:974d5b3d5dce65b4c4ca43b2324ab956e996242d1cf82a0f9c96f9621c9a9890

Observation 20959fb6-6a5b-4938-966b-56cebd8b7c5c · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

LLaVA-c: Continual Improved Visual Instruction Tuning BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.439000Z digest=sha256:185f5d6ea2fb18d7410ac6473c38318fa67c25206896f065ee02d050dc10348d

Observation 053c828f-402a-4ee7-a797-332b586eb3a7 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

LLaVA-c: Continual Improved Visual Instruction Tuning MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 12

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source=pdf_text observed=2026-08-07T05:10:48.444403Z digest=sha256:6a2c1ca526d86fd3b263412c256a1c7832d550a569852ace408179026b6cd4e5

Observation ef89c945-9811-4111-bcbc-231987dbfcfc · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

LLaVA-c: Continual Improved Visual Instruction Tuning InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 13

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no resolver link, observed 2026-08-07T05:10:48.449567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.449567Z digest=sha256:d42d373dc25cfe928f9a9780a8fa7be6f9de21310b9fd7e9217d70a435a88f9e

Observation d3195398-5253-497d-a3c5-705797a42e3e · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Flamingo: a Visual Language Model for Few-Shot Learning

Reference 14

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no resolver link, observed 2026-08-07T05:10:48.454540Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.454540Z digest=sha256:7b64117142f08c2c127b25f4297a742e353bc6cc06bca97837cad54d0e91e65d

Observation bf9ebd97-1d43-4a05-8f04-92367b71005e · outbound

This paper cites Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question Answering.

LLaVA-c: Continual Improved Visual Instruction Tuning Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question Answering

Reference 15

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metadata mismatch
local_arxiv, observed 2026-08-07T05:10:48.709072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.459315Z digest=sha256:21f86a479a0d471d919b9eb6ce604285b3948ef8efc3f40df20012fcf1a4ebe7

Observation d081e199-2a22-4152-88d1-04b1bfa847e4 · outbound

This paper cites Learning visual n-grams from web data.

LLaVA-c: Continual Improved Visual Instruction Tuning Learning visual n-grams from web data

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.136607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.464335Z digest=sha256:3657dd58f103600c5df51cadeb9012b85de59682c9ed367021ffece78e5ba8a9

Observation 3e71fcce-90a6-4474-9b57-62f06d9a5434 · outbound

This paper cites Podnet: Pooled outputs distillation for small-tasks incremental learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Podnet: Pooled outputs distillation for small-tasks incremental learning

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.117957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.469027Z digest=sha256:25d71caf975692d6e254e0d5a87406445b2c442a2d8d15a6b97012f8a7af4f90

Observation 6e29d3ec-3c49-4a68-acc7-7ab8d947ee12 · outbound

This paper cites Learning to prompt for continual learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Learning to prompt for continual learning

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.097712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.473447Z digest=sha256:9f00ff768413cb8a231fba129d81220194a40e47f3240865f039ada4743e04f1

Observation 38fe239b-bdbc-4a5a-b7b7-a6413d62aaa2 · outbound

This paper cites Codaprompt: Co-designing prompt tuning and architecture for continual learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Codaprompt: Co-designing prompt tuning and architecture for continual learning

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.079368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.477929Z digest=sha256:4f8a026d706aa45674d74f93116b6c7654b667aed7d81abb0ce7a500009beb1f

Observation ad74fb26-7df3-4262-b8ce-542710d660da · outbound

This paper cites Kolesnikov, Georg Sperl, and Christoph H.

LLaVA-c: Continual Improved Visual Instruction Tuning Kolesnikov, Georg Sperl, and Christoph H

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.055382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.482554Z digest=sha256:88ffb16e4dcd319ad23fd456adad6d37f197c00d68b256f0dd28a516af0f32c1

Observation 7f3e0243-fec4-41b3-86d8-1336e29a2bff · outbound

This paper cites Wu, Yan-Jia Chen, Lijuan Wang, et al.

LLaVA-c: Continual Improved Visual Instruction Tuning Wu, Yan-Jia Chen, Lijuan Wang, et al

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.032309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.486876Z digest=sha256:bdcf2d0db5ad8ea34ca6138fd90776e48892eef11b2747b4a1e656d094eef36d

Observation 7e420663-6a65-4a19-94bc-10f983836c93 · outbound

This paper cites R-dfcil: Relation-guided representation learning for data-free class incremental learning.

LLaVA-c: Continual Improved Visual Instruction Tuning R-dfcil: Relation-guided representation learning for data-free class incremental learning

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:49.014399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.491116Z digest=sha256:9d4ff9f28eeaf692c33024ca7d2d7296a88ce4c8530a309b14c7b82b11084e43

Observation 2cade2f1-0578-4a2a-9259-3d8b317a042a · outbound

This paper cites Der: Dynamically expandable representation for class incremental learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Der: Dynamically expandable representation for class incremental learning

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.495953Z digest=sha256:bff3922c1a7c5b1f73f53990614baaafa8371a48d259046241f3ba78e87173ef

Observation 6dadac92-a7a2-4ad8-9e4c-1992e04e0b62 · outbound

This paper cites Foster: Feature boosting and compression for class-incremental learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Foster: Feature boosting and compression for class-incremental learning

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.984010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.500845Z digest=sha256:33bd05af1e201861fdbaf910a7a91424c5bb64fbd80b14d6e5a3548abfa4cacd

Observation 7444cb15-c796-4eb6-b0f0-ac525470e9a9 · outbound

This paper cites Dense network expansion for class incremental learning.

LLaVA-c: Continual Improved Visual Instruction Tuning Dense network expansion for class incremental learning

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.966081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.505697Z digest=sha256:7716e03a74a90cb6e571fcd9924918b0bd84aae318202528c65eceeeb2c85d1a

Observation 87967174-5d1d-40e3-a397-a57f8b57c82f · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

LLaVA-c: Continual Improved Visual Instruction Tuning Evaluating Object Hallucination in Large Vision-Language Models

Reference 26

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source=pdf_text observed=2026-08-07T05:10:48.510487Z digest=sha256:ddc155f20bf3fb419db5ce174e7592eb323b857088f7bcc21f978b4f65938e1d

Observation 0e8c0299-a2fe-444a-a299-ec5e852282b6 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

LLaVA-c: Continual Improved Visual Instruction Tuning MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 27

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no resolver link, observed 2026-08-07T05:10:48.515483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.515483Z digest=sha256:42a6ef63053e7b965fe4e7e22c983646e8e21ca75becad4aee8f10d34173f818

Observation 4b4d2220-9067-474d-876f-7cdba0da0ae3 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

LLaVA-c: Continual Improved Visual Instruction Tuning MMBench: Is Your Multi-modal Model an All-around Player?

Reference 28

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no resolver link, observed 2026-08-07T05:10:48.520459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.520459Z digest=sha256:c7e4c08b0e60db1afe3953487c424e15a2ae1836c0a388cc41417abae43eaaf6

Observation 0bedf29d-9374-4e2c-a4db-dc56ddc6feaf · outbound

This paper cites SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension.

LLaVA-c: Continual Improved Visual Instruction Tuning SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 29

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unresolved
no resolver link, observed 2026-08-07T05:10:48.525238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.525238Z digest=sha256:abbf9f4ac05e01b08c652436472d764dc68c58c9346a245732110c5815eed72e

Observation 07117411-9876-4c2d-b492-65ad7e50d52d · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

LLaVA-c: Continual Improved Visual Instruction Tuning MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 30

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no resolver link, observed 2026-08-07T05:10:48.529930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.529930Z digest=sha256:f368f19c8826d141c69d73b4360b9759dc9e4f30c287afef828905345ecda8e0

Observation 28b42e87-f23b-4352-860b-210c29fc50cd · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

LLaVA-c: Continual Improved Visual Instruction Tuning Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 31

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no resolver link, observed 2026-08-07T05:10:48.534756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.534756Z digest=sha256:1c6e4a4681430184ed0213a1a1533f8f58741e944de2c9db519f3b752bde1b33

Observation 44119101-e05a-49bd-8d9d-dc0c0fd78a88 · outbound

This paper cites Super-clevr: A virtual benchmark to diagnose domain robustness in visual reasoning.

LLaVA-c: Continual Improved Visual Instruction Tuning Super-clevr: A virtual benchmark to diagnose domain robustness in visual reasoning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.935367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.540162Z digest=sha256:04e556fa49eebe7364533df862fbba9193ba90b2ea4ad28c2152bc84953f22c4

Observation a87b36ef-58eb-41e7-b5e4-677870ced87f · outbound

This paper cites Iconqa: A new benchmark for abstract diagram understanding and visual language reasoning.

LLaVA-c: Continual Improved Visual Instruction Tuning Iconqa: A new benchmark for abstract diagram understanding and visual language reasoning

Reference 33

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no resolver link, observed 2026-08-07T05:10:48.545072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.545072Z digest=sha256:0a8447453c8072c8bb22e5e6cb52281e2645075bb0d0011f811c91173d77e94f

Observation 406dbe0d-5354-419e-a427-a1f66f65b9b5 · outbound

This paper cites Clevr-math: A dataset for compositional language, visual and mathematical reasoning.

LLaVA-c: Continual Improved Visual Instruction Tuning Clevr-math: A dataset for compositional language, visual and mathematical reasoning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.907081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.549796Z digest=sha256:270d7686f2959edc138781374fb401eab64aa47e3d7138898cbdb5da996d7ab6

Observation b24d8887-5fbe-44ec-be73-56f573a842e2 · outbound

This paper cites Multimodal ArXiv: A dataset for improving scientific comprehension of large vision-language models.

LLaVA-c: Continual Improved Visual Instruction Tuning Multimodal ArXiv: A dataset for improving scientific comprehension of large vision-language models

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.890176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.554512Z digest=sha256:67e61b1310dcb87a1eed07e3a7e9536713de48a2623c46194df865a100fef3df

Observation e594f537-2f6d-450d-9323-91b309ecba89 · outbound

This paper cites FigureQA: An Annotated Figure Dataset for Visual Reasoning.

LLaVA-c: Continual Improved Visual Instruction Tuning FigureQA: An Annotated Figure Dataset for Visual Reasoning

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:48.564186Z digest=sha256:3925d4b4d8f55be44980d0e2048f6e9909c5375fd7122d8e125c9cc62c76e69e

Observation db99883a-7a5c-44b4-89c6-88cfa7c6816b · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

LLaVA-c: Continual Improved Visual Instruction Tuning Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:10:48.855786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.568952Z digest=sha256:3f797b653fccc803badddd553c45e2681c42a2f4d38e96984d0ed15532d190d9

Observation 7806090e-84e6-4469-8fa4-f32da693011a · outbound

This paper cites an unresolved cited work.

LLaVA-c: Continual Improved Visual Instruction Tuning Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:10:48.873025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:10:48.559497Z digest=sha256:0bccbb5f550a151dd63dd34fd460c5c8ee727da42de8698ff13591040d2932c1

Pith citing papers

Observation 16477b54-956d-424c-8519-40a0a847c5a5 · inbound

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 132

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:25.878281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:25.878281Z digest=sha256:9f6e1a905db492801718625a321e766121cab2873f2aa045541be56493a34efd

Observation cbeedfcf-7e66-4eee-b898-3a076d0788f5 · inbound

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training cites this paper.

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T19:31:27.352209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:31:27.352209Z digest=sha256:e112ad0e550bc570d8801ea92eed8baedb717c1611922a5e3c7ef749a7810d14

Observation 636d4818-203b-4936-9b4c-8c855884d30c · inbound

C-NAV: Towards Self-Evolving Continual Object Navigation in Open World cites this paper.

C-NAV: Towards Self-Evolving Continual Object Navigation in Open World LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:35:52.485445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T04:33:13.564547Z digest=sha256:45a7facfaebcca239d0eaab8f4c0cffdb2291d482af129f31e66f15774ffb126

Observation 1880571f-540e-4767-a529-5fc585ededaf · inbound

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning cites this paper.

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T05:33:14.642934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:33:14.642934Z digest=sha256:28f16ffac24c025554be2f3a10bf94b583611e329a0a77322871f091ff609e3c

Observation c34a5874-a9a4-43cd-8c09-c1a8815eca19 · inbound

The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models cites this paper.

The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:15:50.030652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T20:04:46.144856Z digest=sha256:0fa5660cb1685557e3bedbaf32b8ba35ef5e4238b7268d097975e0c18eea29e9

Observation 902ecbab-c9c3-4c63-8082-918a84822cd2 · inbound

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning cites this paper.

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:26:23.210706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T14:18:11.452378Z digest=sha256:8103172b9ea29274b25e897914f7560ace12922a8e72742932fc7e98763b6b7b

Observation aaeed10b-2db5-415b-8842-1d7148317907 · inbound

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning cites this paper.

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:36:17.979536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T15:09:00.320198Z digest=sha256:c33249ddbccf30acc315091011486d0b82a1babdab2c030c44467c3a5075677c

Observation 0317dca0-2546-4685-9303-259b9aeb5184 · inbound

GUI-AC: Enhancing Continual Learning in GUI Agents cites this paper.

GUI-AC: Enhancing Continual Learning in GUI Agents LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:27:36.598107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T13:56:09.049753Z digest=sha256:82467e52627a7aaf4a27d14891050b8899eea2fe21061de874f8f334b65a5982

Observation 57a3f1d4-6027-409d-a69d-0f7828fe4b78 · inbound

GUI-AC: Enhancing Continual Learning in GUI Agents cites this paper.

GUI-AC: Enhancing Continual Learning in GUI Agents LLaVA-c: Continual Improved Visual Instruction Tuning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-07-12T14:27:05.589465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T14:27:05.589465Z digest=sha256:913d9690110223c3a6052e4303ca749eeb780f8ae9f70015d4bc9f8e5bea54ad