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Paper Citation Record · LEDGER

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training

As of 15 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 1 inbound Pith citation observation for arXiv:2505.16875.

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

pith.paper-citation-record.v1
2505.16875 v1

Coverage vector

measured 80 of 80 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:55:59.575885Z

measured 81 of 81 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T21:45:39.346685Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:25:45.885432Z

Reference resolution

80 of 80 outbound references displayed

  • verified exact7
  • verified fuzzy49
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d23fab2d-abc6-47a1-b8b3-f6ce19f4cdb5 · outbound

This paper cites Denton, Seyed Kam- yar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Denton, Seyed Kam- yar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:10.451397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:51.517475Z digest=sha256:71a8b1ab4c4aac17c44b15b433c3fa8e8e4dce761630952b43e23113425ad4e2

Observation 3174e729-9c2e-4178-b654-a243587e74ef · outbound

This paper cites High-resolution image synthesis with latent diffusion models.CVPR, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training High-resolution image synthesis with latent diffusion models.CVPR, 2022

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:10.225332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:51.645874Z digest=sha256:d7675066410e55553f09fb0b0782558aa203c352973001dab38f74d32b437bb0

Observation 18a859ee-763e-4961-862d-6f69615eabe4 · outbound

This paper cites SDXL: improving latent diffusion models for high-resolution image synthesis.ICLR, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training SDXL: improving latent diffusion models for high-resolution image synthesis.ICLR, 2024

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:10.052350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:51.759864Z digest=sha256:0cdf60322ac8b23921ec8e67b0b7bb54a069a9ac16212a7662800ae6304a18da

Observation 8660f1ac-1583-4092-8e17-03544e1cf11b · outbound

This paper cites Kwok, Ping Luo, Huchuan Lu, and Zhenguo Li.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Kwok, Ping Luo, Huchuan Lu, and Zhenguo Li

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:09.788926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:51.859765Z digest=sha256:1c3272be59f811c623182791d7328c858555d71541c75858e7c9bf7c2eaea3c6

Observation 51df0d5d-8c5b-48f3-ae32-9a7a6d160fcc · outbound

This paper cites Pixart- Σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.ECCV, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Pixart- Σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.ECCV, 2024

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:09.605079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:51.951720Z digest=sha256:68be1abad70385ec0ed651ea50135eda57fc803060d520ad918c70b06517575b

Observation 1204c36d-b25a-4ec3-b6dd-64d560252d46 · outbound

This paper cites A survey on personalized content synthesis with diffusion models.arXiv preprint arXiv:2405.05538, 2025.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A survey on personalized content synthesis with diffusion models.arXiv preprint arXiv:2405.05538, 2025

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:52.031267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:52.031267Z digest=sha256:256b65359eda822e4e29f2a3b86950255676693781a90cda4f59881e4e515588

Observation e67113ad-e4c6-4abf-ae6a-1ec712148110 · outbound

This paper cites Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation.CVPR, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation.CVPR, 2023

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:09.325186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:52.179068Z digest=sha256:cb7b07b70c4a2629450adf2bfea6046d01d0059acd577afcca7dbefc210f2a4f

Observation f62206f5-d5d4-4dba-b22f-cfaa5f4a7b71 · outbound

This paper cites Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:52.343614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:52.343614Z digest=sha256:38cae80f8d7a491a58956d044a651af389fe906953e4e64d655e806c39bc9f1b

Observation 70af777a-88be-4473-aef1-0bf49e0cccae · outbound

This paper cites Customizing text-to-image diffusion with object viewpoint control.SIGGRAPH Asia, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Customizing text-to-image diffusion with object viewpoint control.SIGGRAPH Asia, 2024

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:09.114093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:52.465210Z digest=sha256:cd46b6a94b54c3d6152070838679dfcdeebe2fa7024bdd07c8e27246c9e09e0e

Observation 04db9b2b-35b7-4b2f-ae13-644731d47b1b · outbound

This paper cites Diffusion based augmenta- tion for captioning and retrieval in cultural heritage.ICCV (Workshops), 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Diffusion based augmenta- tion for captioning and retrieval in cultural heritage.ICCV (Workshops), 2023

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:08.852828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:52.581574Z digest=sha256:9ae8b8770fd4c5c5c82a54d669be9df5b47d7feeaaf4490cbb90ecaa16510b3e

Observation 797ef686-d5e5-47ae-a984-0ef6433a30c1 · outbound

This paper cites Parameter-efficient transfer learning for NLP.ICML, 2019.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Parameter-efficient transfer learning for NLP.ICML, 2019

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:08.542457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:52.695868Z digest=sha256:8f0f3b0ac14bfad38640080e907460cd2093dcbcb822ee5eaba498d12c1f6046

Observation d7e051f0-fd1d-481d-b3a9-d0143fe6eedd · outbound

This paper cites an unresolved cited work.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:56:08.299598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:52.828119Z digest=sha256:8d120c57b55916db7d6ad98fc20a4bfd7dca94f4bfcd0c2d593fe728c4e607d7

Observation 203a61d0-7a10-4e40-acd9-9e05459748bb · outbound

This paper cites Towards a unified view of parameter-efficient transfer learning.ICLR, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Towards a unified view of parameter-efficient transfer learning.ICLR, 2022

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:08.080248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.002073Z digest=sha256:a8a4841ec4005545a700dcc2449dfd24f905f34ea2c423256a4f5aada4855f9b

Observation b0ad766b-96a0-4900-9632-ae40ff9cd1b9 · outbound

This paper cites Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities.NPJ Computational Materials, 2025.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities.NPJ Computational Materials, 2025

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:07.950358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.166108Z digest=sha256:1a3158273389c738bee188c0f5bb851d0ba1bd7fe541f15986a4f6a0f27ab69c

Observation 20273b34-90d6-41dd-8c3a-7d7ceb5ab7e1 · outbound

This paper cites Continual diffusion: Continual customization of text-to-image diffusion with c-lora.Trans.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual diffusion: Continual customization of text-to-image diffusion with c-lora.Trans

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:07.820304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.257879Z digest=sha256:e003179cf74654b0dfafff134ca227ef8b422a2c99a11fba52ddab31305f627c

Observation 173bc682-3ef1-4664-8d37-e0861e1a3fca · outbound

This paper cites Continual training of language models for few-shot learning.EMNLP, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual training of language models for few-shot learning.EMNLP, 2022

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:07.579488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.441512Z digest=sha256:a72593ff9e0e934117d41bc3bb3cbe621c07f7516fa4553959449c3cbfb34dee

Observation c7d5854b-3eeb-4e0c-9d2a-834a0c23b205 · outbound

This paper cites Continual pre-training of language models.ICLR, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual pre-training of language models.ICLR, 2023

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:07.438455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.581403Z digest=sha256:9c6646b7aa712949cc0e4cbe8e85c0a4bd93cd886b89d995e372077ff9993b9f

Observation 65cc2fbb-c8e9-4cbb-bf6d-415de74a2568 · outbound

This paper cites an unresolved cited work.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:56:07.284173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.698774Z digest=sha256:6a3abba44e78c8f82754bddaa65cb652d7d648724bb3c6d48ecf62420d02662b

Observation 08ed5c58-1740-4f6c-80fb-d10a82d5712d · outbound

This paper cites Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.Psychological Review, 1990.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.Psychological Review, 1990

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:07.113214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.844128Z digest=sha256:0517627d70eb02ded7628f16cdf1fe8f1e21d57efec9ec295cb4cb9ab7961cf7

Observation 5db969ee-bc6f-4a89-91de-6d711c4d6e19 · outbound

This paper cites A comprehensive survey of continual learning: Theory, method and application.IEEE Trans.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A comprehensive survey of continual learning: Theory, method and application.IEEE Trans

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.979547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:53.981603Z digest=sha256:b6fa08cd4e83cc916481df98ffc961b41fde10ff0cc0a08583be8de9e4d03d6f

Observation 6a210583-9fe8-4f7c-9f49-7084d8350af5 · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training On Tiny Episodic Memories in Continual Learning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:54.153379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.153379Z digest=sha256:49f4b4bc5cf18965ba1a73c36efabd6d95e7075742bd3a4502ad1d169d572a1d

Observation 186b16d5-54ac-46cc-aeb6-da1a12a46152 · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.884315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:54.310452Z digest=sha256:cf3de41642137f7a83a0e5a04a9f0ab0b85ab3f0665f9fd799d66a12f0c751de

Observation 19c9bca7-ef7b-46e5-ac57-348212fe775b · outbound

This paper cites Continual learning through synaptic intelligence.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual learning through synaptic intelligence

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.784506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:54.425609Z digest=sha256:5ba8dcb9b1d7d85c33d433cc0cbb362877415c6b04a9d6d53b4402c782e29c2e

Observation ec1c5489-2ffa-44b6-abb0-c0e325919784 · outbound

This paper cites HFT: Half Fine-Tuning for Large Language Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training HFT: Half Fine-Tuning for Large Language Models

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:56:01.233917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:54.497205Z digest=sha256:79b2feb44010a7a7b41a91a1ed8b4b971c8dc59049b2a6d283a1ac68923c6912

Observation 7f2d6a24-a591-4565-bdfa-43056489a3a4 · outbound

This paper cites Mofo: Momentum-filtered optimizer for mitigating forgetting in llm fine-tuning.arXiv preprint arXiv:2407.20999, 2025.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Mofo: Momentum-filtered optimizer for mitigating forgetting in llm fine-tuning.arXiv preprint arXiv:2407.20999, 2025

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:54.564679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.564679Z digest=sha256:73234a785e4ab4e2e0c441206753e87393f17b05d2573895c875fb2dafb4f4d2

Observation 545850d2-c155-4d66-b91d-d078b2b5be0b · outbound

This paper cites Continual Learning of Large Language Models: A Comprehensive Survey.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual Learning of Large Language Models: A Comprehensive Survey

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:54.664729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.664729Z digest=sha256:444665d973b9afe364aaf89a0f753d705e82ac0a0d2866933bd2c4ce35414698

Observation c99c9ed8-f4b3-44b9-b189-617ee7da8129 · outbound

This paper cites TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:54.752131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.752131Z digest=sha256:2ab0a18bfc8d464c666b2071cbf9a32c513b1840386e74181b322d194e62e312

Observation 361e7f10-369e-445b-9629-743c15d2a499 · outbound

This paper cites Dick, and Hidenori Tanaka.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Dick, and Hidenori Tanaka

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.612763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:54.840508Z digest=sha256:65b7464822a83e7318d9ba6012cd46f5305c82a49cff4172a87d005ac7243eee

Observation 4821700b-3221-4c3d-90ef-21acc3e8f15f · outbound

This paper cites Are transformers able to reason by connecting separated knowledge in training data?arXiv preprint arXiv:2501.15857, 2025.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Are transformers able to reason by connecting separated knowledge in training data?arXiv preprint arXiv:2501.15857, 2025

Reference 29

Resolution
verified exact
raw_fallback, observed 2026-08-07T14:56:00.875443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:54.911091Z digest=sha256:a2df19f5feaf218a6f0170cb0dce9c9d93facc14fcb464e9e437f24b65663dfe

Observation 62728e44-29f5-4164-a77e-2742d98220e6 · outbound

This paper cites DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:54.983757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.983757Z digest=sha256:ad299dab8e5c7f01710f6eca048c2de84a80775cbc113e6f9119475b65dedcf9

Observation ad4620b4-725f-4116-9270-0144fc422330 · outbound

This paper cites Diffusion models beat gans on image synthesis.NeurIPS, 2021.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Diffusion models beat gans on image synthesis.NeurIPS, 2021

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.414806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.061507Z digest=sha256:579fedc97df0731eb7186715a83b4e2b6da1e45764ed625d24ebe865b98970c4

Observation 000eaafb-19b1-4c42-875d-2a29e066a897 · outbound

This paper cites T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.NeurIPS, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.NeurIPS, 2023

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.286548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.130564Z digest=sha256:6d4a080ad7a7f4f9fb1a4b773b168394fc99a3784c123f365f1cb284765941fa

Observation 9d260cc7-5d04-4174-a1ff-0f5448c7bb52 · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.NeurIPS, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Geneval: An object-focused framework for evaluating text-to-image alignment.NeurIPS, 2023

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:06.027799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.221542Z digest=sha256:b4e9c63da1b001195572af4713fb4b56ebf70a0e14ec6badcf0918b18f2002c7

Observation 6d8d0bdf-9d60-4941-9007-689761b6ae77 · outbound

This paper cites Dreambench++: A human-aligned benchmark for personalized image generation.ICLR, 2025.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Dreambench++: A human-aligned benchmark for personalized image generation.ICLR, 2025

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:05.876577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.297473Z digest=sha256:88ef792a0ae227dbb67f3ca0fe4ed5421ce025d76cb048eefd1afa55f747432f

Observation 85fb8854-68f7-477e-8750-389b0b445d93 · outbound

This paper cites an unresolved cited work.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:56:05.621265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.387044Z digest=sha256:b8b6853b4f89347c383d058b5b3e3c0f7f23dc8db41fe83ab17c4367e4086f89

Observation 1513644e-1c6e-4ec1-bdd0-d819d3ada8f8 · outbound

This paper cites Synthetic data protection: Towards a paradigm change in data regulation?Big Data Soc., 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Synthetic data protection: Towards a paradigm change in data regulation?Big Data Soc., 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:05.398259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.474381Z digest=sha256:eccd525f18db015855670be2c6821abf7fe8c74db7bc24824d91ab297f90f1d0

Observation 76e9d30c-7d5c-4843-8645-3dac7c7c8cb5 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.NIPS, 2017.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Gans trained by a two time-scale update rule converge to a local nash equilibrium.NIPS, 2017

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:05.212148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.541875Z digest=sha256:74756023d30bbeb244d7977499482fbc0e8c8c4f0b0e41b6aeccf17067b5bd2c

Observation d05114d9-89ac-46bc-a50d-30b0030a0b4c · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:05.011450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.601540Z digest=sha256:fdbdfd45ca7ce4e2cf86b1ce1645f9b004220bb565aaa887bf03d252fb2d71d7

Observation 380a9616-e18a-472a-be36-ed890e532933 · outbound

This paper cites A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:55.660939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:55.660939Z digest=sha256:ad763b73d2d60609e82389cd45897ec004e5ae70202d6aad924e9095571cfdec

Observation eaec64d7-927b-435a-a8a9-a0f65bc980e6 · outbound

This paper cites Minigpt-4: Enhancing vision-language understanding with advanced large language models.ICLR, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Minigpt-4: Enhancing vision-language understanding with advanced large language models.ICLR, 2024

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:04.802881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.742522Z digest=sha256:b4ce9c7bad0500941a930929c85496cd47d8ddad6e7a1d0d4bccd1af4f302b4e

Observation 59926ea7-b4d5-41d8-a191-fa194fd091f7 · outbound

This paper cites Robust visual question answering: Datasets, methods, and future challenges.IEEE Trans.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Robust visual question answering: Datasets, methods, and future challenges.IEEE Trans

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:04.520446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.853593Z digest=sha256:89a5068be708c2b485c1f8e64d1ce24bb8f0f4125216400a8d7e11f1972d0ca4

Observation bddb4821-2d73-4d01-93e8-a3b2897ba1df · outbound

This paper cites Human preference score: Better aligning text-to-image models with human preference.ICCV, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Human preference score: Better aligning text-to-image models with human preference.ICCV, 2023

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:04.288634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:55.928507Z digest=sha256:0fab39c16a676b0efece03b4d39acafb55f4ff56fd3838b191b6ec3d6ed0d9e1

Observation f02fd237-be6d-4468-a3e5-f4d405a9cb4c · outbound

This paper cites A theory for knowledge transfer in continual learning.CoLLAs, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A theory for knowledge transfer in continual learning.CoLLAs, 2022

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:04.098593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.041200Z digest=sha256:ab14111681546caf3d4997a51a59f414964fee02ddc17be1e4bf43e5a17858c4

Observation 20591492-0095-479d-b3b5-9a2cff205e84 · outbound

This paper cites Is multi-task learning an upper bound for continual learning?ICASSP, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Is multi-task learning an upper bound for continual learning?ICASSP, 2023

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:04.002864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.191573Z digest=sha256:bdce78b484b939e32862ce91a274fc69461e442b21a81f551f2556826d3504bf

Observation f096873e-93e4-49bb-88d5-179778eee440 · outbound

This paper cites SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:56.304312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:56.304312Z digest=sha256:cea1ce3138cf56d8ac9e58f691b2d9348d76e69ee88e4ed7d6c9e10fc7cf2b06

Observation 41223eae-84fe-4858-b359-6799d27d0706 · outbound

This paper cites BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:56.404533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:56.404533Z digest=sha256:198e43abb24daf1438f8c2fcc2c2888df8dcea50f9ae8342b2d59ef29514af69

Observation b6c159a8-ed32-4b4c-a0ef-f78fea04467a · outbound

This paper cites A statistical theory of regularization-based continual learning.ICML, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A statistical theory of regularization-based continual learning.ICML, 2024

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.862024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.495903Z digest=sha256:72ab1ba421893ae0d33b2fca47b59f8c5659821edede27607c91f9177183e8e5

Observation 79cb6f1d-f567-4b8f-a3ce-074943793bd6 · outbound

This paper cites Approximate fisher information matrix to characterise the training of deep neural networks.IEEE Trans.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Approximate fisher information matrix to characterise the training of deep neural networks.IEEE Trans

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.733323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.611965Z digest=sha256:e1bf334cd0dbcf44f969dff1bc9f18fac2193eb2c843c473bc025de77db5af0d

Observation e4690716-9cd4-407c-9f58-686bca19fe1a · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding.NAACL-HLT, 2019.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training BERT: pre-training of deep bidirectional transformers for language understanding.NAACL-HLT, 2019

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.617050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.664450Z digest=sha256:33ca43427c9b01f6fbd3150c1a08772804137aa7753b8961d2bc7f0801887435

Observation dc34078c-c284-4710-bd3d-88decc521aa2 · outbound

This paper cites Orthogonal subspace learning for language model continual learning.EMNLP, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Orthogonal subspace learning for language model continual learning.EMNLP, 2023

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.453360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.714533Z digest=sha256:a060037388de39b89261ab378495d378f71c1e19d76b6e79285b76f7693d2db9

Observation d173c5f5-dc6e-4ec7-a750-cb45bf0de7ab · outbound

This paper cites Sutherland.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Sutherland

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.306570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.773040Z digest=sha256:d925330e410b1b272587321728c56210417810d1a8371e05172d01f7e1f44129

Observation 4751c03e-4852-4d28-ae0b-0b6cf8299b16 · outbound

This paper cites LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:56.858393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:56.858393Z digest=sha256:d6cabafbe5fbcf00d397f96fc91c6024319d67f530242ea230c9bd3c834fe35c

Observation 4feba1f3-fd7f-4a8b-b979-c09ec413a74a · outbound

This paper cites Create your world: Lifelong text-to-image diffusion.IEEE Trans.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Create your world: Lifelong text-to-image diffusion.IEEE Trans

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.194563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:56.967629Z digest=sha256:ff39c509a4bd492eaed823e3bd6cade93fb385d4408ec41180bd08f391325cbf

Observation 65cffd4e-310a-4597-8452-78c3530817f4 · outbound

This paper cites Progressive Compositionality in Text-to-Image Generative Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Progressive Compositionality in Text-to-Image Generative Models

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:56:00.580119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.101623Z digest=sha256:e64b379030d5fad9a779c8d10886e4c87d4efd4434b631facd42b2e6ad68a368

Observation e5795070-caca-4424-b3f2-f0e30768f368 · outbound

This paper cites Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:57.193568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:57.193568Z digest=sha256:4d8c056b36a3bc3ea4f29976ae4f936b1b2e1c0d9b833871a5f39e3d3aabad1a

Observation 93e6205a-ce89-4085-8d55-6a02a9a8db53 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.MICCAI, 2015.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training U-net: Convolutional networks for biomedical image segmentation.MICCAI, 2015

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:03.036965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.309777Z digest=sha256:e10240d483c4eb71ac05963dee077d5213b7968ea0d07ba8c366e9cfd506a28f

Observation abe635c4-395a-4254-9cd9-8fd9e9a24186 · outbound

This paper cites Learning transferable visual models from natural language supervision.ICML, 2021.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Learning transferable visual models from natural language supervision.ICML, 2021

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.925943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.432683Z digest=sha256:85d9a81bb5461043a619c5fcfdb1397b00f2d3198c97e71c86543a35863a0392

Observation 8c5846e6-16ad-4093-ae14-24dc7a801559 · outbound

This paper cites Improving image captioning with better use of captions.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Improving image captioning with better use of captions

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.781614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.534004Z digest=sha256:755352b1bb537ecdf6282874fe2b69bccc975a447ab79d1abeb1737aa921079a

Observation c396b7a4-0876-4115-a01a-434955f1c288 · outbound

This paper cites Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:57.615254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:57.615254Z digest=sha256:cd6fe83c0b8ba58c1d1a6255f6c4721f70e25d366fb85d1ae44faec49f8ce18f

Observation 26c47138-98a0-4539-a7bc-ed3b37c287de · outbound

This paper cites Identity Encoder for Personalized Diffusion.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Identity Encoder for Personalized Diffusion

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:56:00.382547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.728252Z digest=sha256:a3ec0cfecfe40e04682f2e5a93cd6b680908de762a4e5b35ec44f231898c7754

Observation 148f1bdc-9f15-49b3-bda3-7a37b137f8ab · outbound

This paper cites Prompt-to- prompt image editing with cross attention control.ICLR, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Prompt-to- prompt image editing with cross attention control.ICLR, 2022

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.658634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.843922Z digest=sha256:73162b45b409b3455602e37a42c9cb25d32ee130a83f78e75dd929ec8d8da131

Observation aec9f678-4e23-42ab-9cb6-f750344a45bd · outbound

This paper cites Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:56:00.206036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:57.994758Z digest=sha256:06a969a72246138f70a7b7e17e84681eb4c9c45147285ba6c48f20f19d64db02

Observation 73d02449-732d-4cdd-be17-597e7ef674f0 · outbound

This paper cites Diffboost: Enhancing medical image segmentation via text-guided diffusion model.IEEE Transactions on Medical Imaging, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Diffboost: Enhancing medical image segmentation via text-guided diffusion model.IEEE Transactions on Medical Imaging, 2024

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.481446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.082897Z digest=sha256:279c8c8528f2a1d6c03f8a13f9b5aac47412a0de69c4f35996daa03207ed9d27

Observation dd1a52c2-82d4-4827-ad77-2727bf025231 · outbound

This paper cites Diffportrait3d: Controllable diffusion for zero-shot portrait view synthesis.CVPR, 2024.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Diffportrait3d: Controllable diffusion for zero-shot portrait view synthesis.CVPR, 2024

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.373784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.222437Z digest=sha256:47e63e59f05fbda3f23e7771c48b62de866c62b4db9112d40e879cc0d2f9d9ff

Observation 20084761-37c5-427b-91d4-b3346620be5f · outbound

This paper cites Towards High-Fidelity 3D Portrait Generation with Rich Details by Cross-View Prior-Aware Diffusion.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Towards High-Fidelity 3D Portrait Generation with Rich Details by Cross-View Prior-Aware Diffusion

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:56:00.083520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.293323Z digest=sha256:03b7906715efe630108f242c5649c4e03cf80b5e7c635bf232379be1af929f04

Observation 1949151f-277f-4b49-88c0-3d7e6ed9c1a0 · outbound

This paper cites A Note on the Inception Score.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training A Note on the Inception Score

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:58.393757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:58.393757Z digest=sha256:635d6266b32492fe670922cb3c582cfdde3da5ab310ab0559c23fde655c806e5

Observation e739c3e5-5862-48e3-973b-f5ef1c9854e7 · outbound

This paper cites Rethinking the inception architecture for computer vision.CVPR, 2016.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Rethinking the inception architecture for computer vision.CVPR, 2016

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.257577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.467808Z digest=sha256:285abf18d6c752ead18552f17fb4782b7f114dcd83d44d55c63f45e08f9b35d9

Observation 6ed43eed-1b59-4073-bece-503dbbb05975 · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Efros, Eli Shechtman, and Oliver Wang

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:02.129482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.539403Z digest=sha256:f26b0f297e59c1be8f142a478223b4b3a80fc055dfd901bf267b4a2681120fc6

Observation 2c6e5f04-5d01-4f3a-83e7-c3f939092d41 · outbound

This paper cites Emerging properties in self-supervised vision transformers.ICCV, 2021.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Emerging properties in self-supervised vision transformers.ICCV, 2021

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:01.990027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.637434Z digest=sha256:15bdedcfd6a62019bf8b5cbd6ec7c4fdf1674eeaa39f5440202f77d76225c3ba

Observation 10d05be9-749f-4ea1-ba86-ef8fe8009100 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.ICML, 2022.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.ICML, 2022

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:01.828516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.729885Z digest=sha256:8d314a47bfcc888c0bce486070710a369f44943732fb66d33753ee2d4ccbd87c

Observation af00fe6c-ad4f-42f1-a4c8-7853dd2c0a11 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.NeurIPS, 2023.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Imagereward: Learning and evaluating human preferences for text-to-image generation.NeurIPS, 2023

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:01.654289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:58.849018Z digest=sha256:e0754a6463f45f24239cc1164871e015a84a7666802134dbcd6f85900f60f8c4

Observation 547e8f05-0e97-403a-8a92-94de89e4a92b · outbound

This paper cites CLoG: Benchmarking Continual Learning of Image Generation Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training CLoG: Benchmarking Continual Learning of Image Generation Models

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:58.931222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:58.931222Z digest=sha256:a2c599637bcccaf6abcffb8bde5a4513fa2c73ba2fa5821d13cbe0d6f1b770ad

Observation cc794c2a-1090-458f-8f31-9925d481eee4 · outbound

This paper cites DeepSeek-V3 Technical Report.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training DeepSeek-V3 Technical Report

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.037860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.037860Z digest=sha256:f165f08e75e8325d5ba38b373b6c121dbccafda600e5f92564a79e775b81d89c

Observation f4949118-8bc3-42e1-8e38-a6bc94b423b7 · outbound

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

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.082383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.082383Z digest=sha256:40ebf44c359da4b2268d450e1a3bdc59f4b007b3be0ee494543848a5cce73164

Observation 74cb58b1-0377-442b-8756-2d682f9ae20e · outbound

This paper cites Qwen2.5 Technical Report.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Qwen2.5 Technical Report

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.179186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.179186Z digest=sha256:afbb9bc21ca087322c27e1f9bde6825dc9767d0d58023b4a7976afbc6b50953a

Observation 61b360f0-ea25-4bb4-a401-d2d259f58d2c · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.290217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.290217Z digest=sha256:a2c00acd6d51570cd51d2dcea446d4ca1e6296420ace6f481b20b91aebe18e5c

Observation b058e921-b167-4e20-980e-3ac2278c6f46 · outbound

This paper cites Kingma and Jimmy Ba.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Kingma and Jimmy Ba

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:01.466920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:59.364506Z digest=sha256:f85b44d53b041e59d7ac0e5a8b6ab8f46b2814abedba0ab8c7f7f59212da67a7

Observation cd6ba267-fb86-4c85-b355-b7f53185af27 · outbound

This paper cites ZeRO: Memory Optimizations Toward Training Trillion Parameter Models.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.441095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.441095Z digest=sha256:6123fc0c616d8ae58aacf04f1d49911aaa34a6a8d5a191282e9236834d166c1c

Observation 039c1cd3-c8dd-4572-a342-66740d4a06d2 · outbound

This paper cites Decoupled weight decay regularization.ICLR, 2019.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Decoupled weight decay regularization.ICLR, 2019

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:59.520935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:59.520935Z digest=sha256:283cc3fc3ecfa589e3c620212358a091523a5f0ec0d7c1e5ffce82227dfb9140

Observation 7a7249be-c7cc-42c2-a2f4-c03b4ca4b1ad · outbound

This paper cites item customization.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training item customization

Reference 80

Resolution
verified exact
raw_fallback, observed 2026-08-07T14:55:59.807812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T14:55:59.575885Z digest=sha256:80675d59455afdb2265dff543c50920992d14d50af5196f190a4f323534486ac

Pith citing papers

Observation bcf2e8cd-7e24-443b-a4cf-19418b885837 · inbound

ACE-LoRA: Adaptive Orthogonal Decoupling for Continual Image Editing cites this paper.

ACE-LoRA: Adaptive Orthogonal Decoupling for Continual Image Editing T2I-ConBench: Text-to-Image Benchmark for Continual Post-training

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:25:45.886881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T21:45:39.346685Z digest=sha256:d07c2405504fb9b46f093ae395868561f1db22ac4f4ea9d30a5d12c472fcd414