Zero-Shot Vision Encoder Grafting via LLM Surrogates | Paper Citation Record

Observation 260503fb-70c9-419e-9346-d45496269371 · outbound

This paper cites Understanding Inter- mediate Layers Using Linear Classifier Probes.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Understanding Inter- mediate Layers Using Linear Classifier Probes

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:24.280642Z

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 a5d9bd1d-3cfd-476b-8415-2836dd75b673 · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates Flamingo: a Visual Language Model for Few-Shot Learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:23.894969Z

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Observation 9544eb4d-59cd-40dc-a31a-a6342a5cd088 · outbound

This paper cites Eliciting Latent Predictions from Transformers with the Tuned Lens.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Eliciting Latent Predictions from Transformers with the Tuned Lens

Reference 3

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Observation 362a970d-0fc7-457c-9579-d940edc8e5a0 · outbound

This paper cites PIQA: Reasoning about Physical Commonsense in Natural Language.

Zero-Shot Vision Encoder Grafting via LLM Surrogates PIQA: Reasoning about Physical Commonsense in Natural Language

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:23.407238Z

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Observation 0038ccda-7977-4d22-928b-75fbc3ad31fe · outbound

This paper cites GenQA: Generating Millions of Instructions from a Handful of Prompts.

Zero-Shot Vision Encoder Grafting via LLM Surrogates GenQA: Generating Millions of Instructions from a Handful of Prompts

Reference 5

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Observation 23ecf2b9-8082-4abd-9ce3-97b81ab43e7a · outbound

This paper cites InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks.

Zero-Shot Vision Encoder Grafting via LLM Surrogates InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:23.087790Z

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Observation 15b07d9f-64ed-41f7-9924-daad416ba5bc · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

Zero-Shot Vision Encoder Grafting via LLM Surrogates BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:22.825369Z

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Observation d5b5b0a8-89d3-4666-8664-009a8d53eee2 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:04.718039Z

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Observation 01fa7e38-1e5d-4ef9-93a5-901f89510876 · outbound

This paper cites The Llama 3 Herd of Models.

Zero-Shot Vision Encoder Grafting via LLM Surrogates The Llama 3 Herd of Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:04.898522Z

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Observation 5b4a33fc-eb7a-4283-b220-365723fedb31 · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:04.974166Z

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Observation 551b002b-ce61-45cd-b6e5-ac28a7b6aded · outbound

This paper cites A Framework for Few-Shot Language Model Evaluation, 2024.

Zero-Shot Vision Encoder Grafting via LLM Surrogates A Framework for Few-Shot Language Model Evaluation, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:22.629018Z

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Observation d1a63bc4-cf48-4255-bdb5-778f03175f2e · outbound

This paper cites The Unreasonable Ineffectiveness of the Deeper Layers.

Zero-Shot Vision Encoder Grafting via LLM Surrogates The Unreasonable Ineffectiveness of the Deeper Layers

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:22.422088Z

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Observation b946c6a1-1a01-4cf3-a6f8-e9132388e955 · outbound

This paper cites VizWiz Grand Challenge: Answering Visual Questions from Blind People.

Zero-Shot Vision Encoder Grafting via LLM Surrogates VizWiz Grand Challenge: Answering Visual Questions from Blind People

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:22.118148Z

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Observation b82948d8-89bc-4133-8fea-961338574cef · outbound

This paper cites Word Embed- dings Are Steers for Language Models.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Word Embed- dings Are Steers for Language Models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:21.805678Z

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Observation 59cedae0-882b-4c12-8981-88ae6f07fd93 · outbound

This paper cites Measur- ing Massive Multitask Language Understanding.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Measur- ing Massive Multitask Language Understanding

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:21.475285Z

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Observation 23bde0c7-c291-4500-a284-599a88ae5017 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Zero-Shot Vision Encoder Grafting via LLM Surrogates LoRA: Low-Rank Adaptation of Large Language Models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:21.140630Z

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Observation 649794ba-112a-4f81-bc14-897e75708ce8 · outbound

This paper cites GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering.

Zero-Shot Vision Encoder Grafting via LLM Surrogates GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:20.845832Z

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Observation eb6c8812-05c5-41e1-95f8-1d5eee1132ef · outbound

This paper cites InternVL2: Better than the Best—Expanding Performance Boundaries of Open-Source Multimodal Mod- els with the Progressive Scaling Strategy.

Zero-Shot Vision Encoder Grafting via LLM Surrogates InternVL2: Better than the Best—Expanding Performance Boundaries of Open-Source Multimodal Mod- els with the Progressive Scaling Strategy

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:20.536709Z

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Observation c7be7e24-b793-42cf-a693-fd05281938c6 · outbound

This paper cites A Diagram Is Worth a Dozen Images.

Zero-Shot Vision Encoder Grafting via LLM Surrogates A Diagram Is Worth a Dozen Images

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:20.238302Z

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Observation 51e4d9b8-f8e7-47e3-85ef-fb41ceeaaa29 · outbound

This paper cites Propulsion: Steering LLM with Tiny Fine-Tuning.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Propulsion: Steering LLM with Tiny Fine-Tuning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:19.880653Z

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

Observation dc51ade7-865f-494a-813a-e740ae092e60 · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates SEED-Bench: Benchmarking Multi- modal LLMs with Generative Comprehension

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:19.640428Z

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Observation ef148f84-4a47-4d82-8ed6-8b250a7c0ea5 · outbound

This paper cites LLaV A-Next: Stronger Llms Supercharge Multimodal Capabilities in the Wild.

Zero-Shot Vision Encoder Grafting via LLM Surrogates LLaV A-Next: Stronger Llms Supercharge Multimodal Capabilities in the Wild

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:19.339366Z

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Observation 7832c4fa-c5e8-4888-b070-8974240f4229 · outbound

This paper cites LMMs-Eval: Accelerating the Development of Large Multimodal Models.

Zero-Shot Vision Encoder Grafting via LLM Surrogates LMMs-Eval: Accelerating the Development of Large Multimodal Models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:19.028093Z

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Observation c0410ddb-23dc-45dd-848c-d1419c58cf19 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

Zero-Shot Vision Encoder Grafting via LLM Surrogates LLaVA-OneVision: Easy Visual Task Transfer

Reference 24

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Observation 0755a51f-eaac-4b00-9b4c-3239e119c8f5 · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:18.689949Z

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

Observation 3e3532c1-4f67-4bb3-a78f-3d463911b73a · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates Evaluating Object Hallucination in Large Vision-Language Models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:18.346769Z

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 c9b6ce0f-78ed-4883-bbb3-dec8e561454a · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Improved Baselines with Visual Instruction Tuning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:18.009253Z

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

Observation 9dd22051-41b2-4fad-9ab1-324a36a2e708 · outbound

This paper cites LLaV A-Next: Im- proved Reasoning, Ocr, and World Knowledge.

Zero-Shot Vision Encoder Grafting via LLM Surrogates LLaV A-Next: Im- proved Reasoning, Ocr, and World Knowledge

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:17.719998Z

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Observation b193148e-e3df-4f21-a0fd-15b2cdf9772e · outbound

This paper cites Visual Instruction Tuning.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Visual Instruction Tuning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:17.431218Z

Source-reported events for the cited work

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Observation c245efa1-3580-47e7-ba77-2bcc3340a6bd · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player? In ECCV, 2025.

Zero-Shot Vision Encoder Grafting via LLM Surrogates MMBench: Is Your Multi-modal Model an All-around Player? In ECCV, 2025

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:17.038114Z

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Observation 54401c49-46c3-4af6-b992-1fdc4d582771 · outbound

This paper cites Chartqa: A Benchmark for Question Answering About Charts With Visual and Logical Reason- ing.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Chartqa: A Benchmark for Question Answering About Charts With Visual and Logical Reason- ing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:16.743903Z

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 4c64e431-059d-4041-88f4-0bf1cb177edd · outbound

This paper cites Docvqa: A Dataset for VQA on Document Images.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Docvqa: A Dataset for VQA on Document Images

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:16.373407Z

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 a9d22fad-abc7-49d9-810f-a284bbfe4824 · outbound

This paper cites Infograph- icVQA.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Infograph- icVQA

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:16.063658Z

Source-reported events for the cited work

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Observation b2bdd531-cbc6-4173-bb5f-290a138497d0 · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

Zero-Shot Vision Encoder Grafting via LLM Surrogates ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:08.563542Z

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Observation 6cdc855b-7bfd-4691-801c-425a5f9c46f5 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:15.729807Z

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Observation 232146ff-0a88-4f50-855c-fb474f1916d3 · outbound

This paper cites interpreting GPT: the logit lens.

Zero-Shot Vision Encoder Grafting via LLM Surrogates interpreting GPT: the logit lens

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:15.404758Z

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 70fe4b8e-5a8c-4c2e-ac06-9159051c07fa · outbound

This paper cites Learning Transferable Visual Models From Natural Language Super- vision.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Learning Transferable Visual Models From Natural Language Super- vision

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:15.037846Z

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 a54574e4-0195-4a87-b106-2c4102115b3f · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

Zero-Shot Vision Encoder Grafting via LLM Surrogates WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:14.688023Z

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Observation 919f7776-77bc-4d98-9e36-159147c403cf · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Open Problems in Mechanistic Interpretability

Reference 39

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Observation 78f61f07-327e-420c-a7aa-9e2c43699f45 · outbound

This paper cites Towards VQA Models That Can Read.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Towards VQA Models That Can Read

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:14.377820Z

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Observation ae21e43a-ad87-459a-96a4-d61fe2ab610b · outbound

This paper cites Transformer Layers as Painters.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Transformer Layers as Painters

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:09.868806Z

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Observation c2eeae5e-c64c-4045-9a0d-fe116ec56739 · outbound

This paper cites an unresolved cited work.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:10:14.074467Z

Source-reported events for the cited work

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Observation 8b80db9e-b15a-49f8-9293-6e6b9916aaad · outbound

This paper cites an unresolved cited work.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:10:13.774364Z

Source-reported events for the cited work

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Observation a5233e1d-bf72-455f-9bde-cbcffb59e415 · outbound

This paper cites Qwen2.5 Technical Report.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Qwen2.5 Technical Report

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:10.316669Z

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Observation 8cac2992-8ccd-4fe4-b59d-3433f20693fb · outbound

This paper cites Qwen3 Technical Report.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Qwen3 Technical Report

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:10.411364Z

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Unavailable: canonical work link unavailable.

Observation 9a9ab4b5-bf59-4450-99bf-fbc4ddfbb156 · outbound

This paper cites Cambrian- 1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Cambrian- 1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:13.491774Z

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Observation bbd238ab-8814-446f-beb0-b6b14efeb168 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

Zero-Shot Vision Encoder Grafting via LLM Surrogates SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:10.711035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02bcb860-639e-41f6-b365-d8f131348935 · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:10.917149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90da24bf-cbc8-4556-ad96-05125bcc443d · outbound

This paper cites CogVLM: Visual Expert for Pretrained Lan- guage Models.

Zero-Shot Vision Encoder Grafting via LLM Surrogates CogVLM: Visual Expert for Pretrained Lan- guage Models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:13.221500Z

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 5a1b519c-ef56-4100-9df7-56f6a70460de · outbound

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

Zero-Shot Vision Encoder Grafting via LLM Surrogates MM-Vet: Evaluating Large Multimodal Models for Inte- grated Capabilities

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:12.806130Z

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

Observation 9f4c83da-0827-4fb2-b03c-2602aeeaa9b4 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence? In ACL Anthology, 2019.

Zero-Shot Vision Encoder Grafting via LLM Surrogates HellaSwag: Can a Machine Really Finish Your Sentence? In ACL Anthology, 2019

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:12.491448Z

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Observation 652f85e5-fdfb-400c-be5a-0ee75c053fec · outbound

This paper cites Sigmoid Loss for Language Image Pre- Training.

Zero-Shot Vision Encoder Grafting via LLM Surrogates Sigmoid Loss for Language Image Pre- Training

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:10:12.138345Z

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 f1dca64a-039e-41c8-b879-848cd520fce3 · outbound

This paper cites PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Zero-Shot Vision Encoder Grafting via LLM Surrogates PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

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