Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts | Paper Citation Record

Observation 6e2e8eea-796d-4368-8b41-c56caa12cd8a · outbound

This paper cites LLM2Vec: Large language models are secretly powerful text encoders.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts LLM2Vec: Large language models are secretly powerful text encoders

Reference 1

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

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Internvl: Scal- ing up vision foundation models and aligning for generic visual-linguistic tasks

Reference 2

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Observation 2625b4d0-cc90-4148-a31f-a0ea6ef61f4e · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Reproducible scaling laws for contrastive language-image learning

Reference 3

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This paper cites The case for human–AI interaction as system 0 thinking.Nature Human Behaviour, 8(10):1829–1830.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts The case for human–AI interaction as system 0 thinking.Nature Human Behaviour, 8(10):1829–1830

Reference 4

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Observation d6ccb2da-6fd5-4311-b054-f2591cca8b8b · outbound

This paper cites Distribution-aware prompt tuning for vision-language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Distribution-aware prompt tuning for vision-language models

Reference 5

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Observation 257b2f58-219b-4707-8850-d367bebea814 · outbound

This paper cites Exploring large language models for multi-modal out-of-distribution detection.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Exploring large language models for multi-modal out-of-distribution detection

Reference 6

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Observation 9d979047-2322-4bb7-8839-c9ef64d7f547 · outbound

This paper cites Qlora: Efficient finetuning of quan- tized llms.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Qlora: Efficient finetuning of quan- tized llms

Reference 7

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Observation 6e9e945e-d466-4e30-900a-527bf5e2e8ab · outbound

This paper cites Unveiling encoder- free vision-language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Unveiling encoder- free vision-language models

Reference 8

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Observation cf1a2418-de86-4ba0-8669-0e3b96c97e46 · outbound

This paper cites A survey on in-context learning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts A survey on in-context learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.225202Z

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Observation 49cf2a4c-a816-4917-8eec-e74ed2fddbd5 · outbound

This paper cites CCG: Rare-label prediction via neu- ral SEM–driven causal game.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts CCG: Rare-label prediction via neu- ral SEM–driven causal game

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.231394Z

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Observation 79b66bf9-aea1-449c-a6a8-283d765ac7da · outbound

This paper cites CLIP-Adapter: Better Vision-Language Models with Feature Adapters.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Reference 11

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Observation 9e9ee1ad-8538-4d75-91e2-90463c4fe7e7 · outbound

This paper cites Context encoders as a simple but powerful extension of word2vec.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Context encoders as a simple but powerful extension of word2vec

Reference 12

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Observation 04da7ef7-adc0-4e5b-89f2-8e6e719e4568 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Parameter-efficient transfer learning for nlp

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.114136Z

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This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.106109Z

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Observation 26eb4722-f348-41fb-854e-57eb76abc5fc · outbound

This paper cites Le, Yunhsuan Sung, Zhen Li, and Tom Duerig.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Le, Yunhsuan Sung, Zhen Li, and Tom Duerig

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.164577Z

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Observation a0799031-45bf-4fea-8320-390d1c515b57 · outbound

This paper cites Visual prompt tuning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Visual prompt tuning

Reference 16

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Observation 9d9c9612-ab6a-4208-baca-d581988adfac · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts The power of scale for parameter-efficient prompt tuning

Reference 17

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This paper cites Selvaraju, Akhilesh Deepak Gotmare, Shafiq Joty, Caiming Xiong, and Steven Hoi.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Selvaraju, Akhilesh Deepak Gotmare, Shafiq Joty, Caiming Xiong, and Steven Hoi

Reference 18

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This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and gener- ation.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Blip: Bootstrapping language-image pre-training for unified vision-language understanding and gener- ation

Reference 19

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Observation f3f66739-32c3-40c4-9d61-120ff9c0a6a5 · outbound

This paper cites Im- proving the accuracy of diabetes diagnosis applica- tions through a hybrid feature selection algorithm.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Im- proving the accuracy of diabetes diagnosis applica- tions through a hybrid feature selection algorithm

Reference 20

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Observation bf90cc97-045a-4fc4-aaa5-f04c88504b7f · outbound

This paper cites Distilling large vision- language model with out-of-distribution generalizabil- ity.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Distilling large vision- language model with out-of-distribution generalizabil- ity

Reference 21

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Observation 7438f7ed-ab49-4ccc-8498-bdba14221b51 · outbound

This paper cites Visual instruction tuning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Visual instruction tuning

Reference 22

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Observation e49a8ce3-205e-423d-9617-af4cc9560d9e · outbound

This paper cites Towards out-of- distribution generalization: A survey.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Towards out-of- distribution generalization: A survey

Reference 23

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This paper cites Mta: Multimodal task alignment for bev perception and captioning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Mta: Multimodal task alignment for bev perception and captioning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.235802Z

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This paper cites Adavit: Adaptive vision transformers for efficient im- age recognition.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Adavit: Adaptive vision transformers for efficient im- age recognition

Reference 25

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Observation fa0187ce-612a-49f1-a773-60a40df87bff · outbound

This paper cites Gpt-4 technical report.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Gpt-4 technical report

Reference 26

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This paper cites Learning to name classes for vision and language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Learning to name classes for vision and language models

Reference 27

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This paper cites Qwen2.5 technical report.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Qwen2.5 technical report

Reference 28

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Observation 8dabe4dd-b48f-4faa-801b-0b1625355c06 · outbound

This paper cites Learning trans- ferable visual models from natural language supervi- sion.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Learning trans- ferable visual models from natural language supervi- sion

Reference 29

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This paper cites Denseclip: Language-guided dense predic- tion with context-aware prompting.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Denseclip: Language-guided dense predic- tion with context-aware prompting

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.135258Z

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This paper cites Laion-400m: Open dataset of clip-filtered 400 million image-text pairs.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Laion-400m: Open dataset of clip-filtered 400 million image-text pairs

Reference 31

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This paper cites How Much Can CLIP Benefit Vision-and-Language Tasks?.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 32

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This paper cites Human cognition involves the dynamic integra- tion of neural activity and neuromodulatory systems.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Human cognition involves the dynamic integra- tion of neural activity and neuromodulatory systems

Reference 33

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This paper cites Fastcontext: Han- dling out-of-vocabulary words using the word struc- ture and context.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Fastcontext: Han- dling out-of-vocabulary words using the word struc- ture and context

Reference 34

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This paper cites Out- of-distribution generalization via composition: a lens through induction heads in transformers.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Out- of-distribution generalization via composition: a lens through induction heads in transformers

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.149394Z

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Observation 48a14aa2-1f7e-46a0-b231-8db2ce0c06d4 · outbound

This paper cites Robust fine-tuning of vision-language models for domain generalization.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Robust fine-tuning of vision-language models for domain generalization

Reference 36

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This paper cites Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, An- drew M.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, An- drew M

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.129644Z

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This paper cites Robust fine-tuning of zero-shot models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Robust fine-tuning of zero-shot models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.110969Z

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Observation 12c317bc-ab5d-40b4-bb6f-a0289a0bf8f1 · outbound

This paper cites Cascade prompt learning for vision-language model adaptation.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Cascade prompt learning for vision-language model adaptation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.223189Z

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Observation 714903af-a364-443b-8b14-2d5f3516e4c3 · outbound

This paper cites Depthssc: Monocular 3d seman- tic scene completion via depth-spatial alignment and voxel adaptation.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Depthssc: Monocular 3d seman- tic scene completion via depth-spatial alignment and voxel adaptation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.229235Z

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This paper cites Task residual for tuning vision-language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Task residual for tuning vision-language models

Reference 41

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Observation a70f43dc-d0f5-482a-a52c-a29a323c0a31 · outbound

This paper cites Boosting vision-language models with transduction.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Boosting vision-language models with transduction

Reference 42

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Observation d5a116c5-5593-46cc-8db3-daaac8cb9b06 · outbound

This paper cites MAT-agent: Adaptive multi- agent training optimization.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts MAT-agent: Adaptive multi- agent training optimization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.132287Z

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Observation f388a372-2a37-44ce-9fa0-d3c2736ca977 · outbound

This paper cites CF-VLM: Counterfactual vision- language fine-tuning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts CF-VLM: Counterfactual vision- language fine-tuning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.204078Z

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Observation 0c8288ed-62a0-41a8-90bb-5117b52ca4e4 · outbound

This paper cites Mm-cot:a benchmark for probing visual chain- of-thought reasoning in multimodal models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Mm-cot:a benchmark for probing visual chain- of-thought reasoning in multimodal models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.144630Z

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Observation 6a5b94a0-cc9a-4c77-87a4-9c0ab7dc7edf · outbound

This paper cites Top-down semantic refinement for image captioning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Top-down semantic refinement for image captioning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.189353Z

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Observation 6f0ab9c0-3e40-41a8-bf3b-b08e17ab58cf · outbound

This paper cites Learning dynamics of vlm finetuning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Learning dynamics of vlm finetuning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.210861Z

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Observation 4a42b339-502e-48e2-85c3-4580f322ecea · outbound

This paper cites Failure-driven workflow refinement.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Failure-driven workflow refinement

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.127166Z

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Observation b95129dc-d585-4487-b910-99d39ad44881 · outbound

This paper cites Drdiff: Dynamic routing diffusion with hierarchical attention for breaking the efficiency- quality trade-off.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Drdiff: Dynamic routing diffusion with hierarchical attention for breaking the efficiency- quality trade-off

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.219455Z

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Observation 11ca9b48-397a-42ab-88cb-e323c5253417 · outbound

This paper cites Osc: Cognitive orchestration through dynamic knowledge alignment in multi-agent llm col- laboration.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Osc: Cognitive orchestration through dynamic knowledge alignment in multi-agent llm col- laboration

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.197878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2a008d58-cdfd-4f16-b677-416dabbe0816 · outbound

This paper cites Kolmogorov-arnold fourier networks.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Kolmogorov-arnold fourier networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.173626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 83d5bc85-bab5-40dd-82ea-bff7f9105299 · outbound

This paper cites GAM-agent: Game-theoretic and uncertainty- aware collaboration for complex visual reasoning.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts GAM-agent: Game-theoretic and uncertainty- aware collaboration for complex visual reasoning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.185506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42282af2-1042-48d8-8c6b-48bf4143c132 · outbound

This paper cites Tri-MARF: A tri-modal multi-agent re- sponsive framework for comprehensive 3d object an- notation.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Tri-MARF: A tri-modal multi-agent re- sponsive framework for comprehensive 3d object an- notation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.116732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cc800b2d-9b27-419a-bab8-bad389be027b · outbound

This paper cites Hybridtoken-vlm: Hybrid token compression for vision-language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Hybridtoken-vlm: Hybrid token compression for vision-language models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.137597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e09a9218-b6d6-40f8-8ad0-ba479042c690 · outbound

This paper cites KABB: Knowledge-aware bayesian bandits for dynamic expert coordination in multi-agent systems.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts KABB: Knowledge-aware bayesian bandits for dynamic expert coordination in multi-agent systems

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.217384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 280f4ccb-04bd-4f7f-b8a7-09a3de7e1aae · outbound

This paper cites Llm-cas: Dynamic neuron perturbation for real-time hallucination correction.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Llm-cas: Dynamic neuron perturbation for real-time hallucination correction

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.206492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d2c9a1f-aa02-467c-9b45-7b8e37db11c3 · outbound

This paper cites Llava-read: Enhanc- ing reading ability of multimodal language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Llava-read: Enhanc- ing reading ability of multimodal language models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.157841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4affe112-4d36-48b9-a74f-722dffdac858 · outbound

This paper cites Learn- ing from models beyond fine-tuning.Nature Machine Intelligence, 7(1):6–17.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Learn- ing from models beyond fine-tuning.Nature Machine Intelligence, 7(1):6–17

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.120013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 664360d9-6296-44ce-aefd-770229c79ca8 · outbound

This paper cites Conditional prompt learning for vision- language models.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Conditional prompt learning for vision- language models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.178620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 82042918-f9c9-4587-a4ac-c07b8b1d34db · outbound

This paper cites Learning to prompt for vision-language models.International Journal of Computer Vision, 130(9):2337–2348.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts Learning to prompt for vision-language models.International Journal of Computer Vision, 130(9):2337–2348

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T15:23:02.193665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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