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Paper Citation Record · LEDGER

Zero-Shot Vision Encoder Grafting via LLM Surrogates

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2505.22664.

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

pith.paper-citation-record.v1
2505.22664 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:10:11.740399Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy37
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:03.570614Z digest=sha256:add451fecd9b893aec8fcabe41f21a88f0ac4fe4f0849cc9ff37cedb0a110d16

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:03.714649Z digest=sha256:06a4c9a8ca6db82b14410d60582529663664686d66668f5321fd39434a4480a9

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:03.928054Z digest=sha256:6a50b3f0ec4f5d3eb96b1474eb214cf7a0a95b112061b8175f49401247d464b4

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:04.074749Z digest=sha256:6f74862cee582ebf05b9b281aead883ebc59bb392631afe432e0af0ad1632b6c

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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no resolver link, observed 2026-08-07T13:10:04.258432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:04.258432Z digest=sha256:c773b3d0bc59c8a8215c3a9584480cba81d85338e21f1a55122cd68a072bdcb4

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:04.453895Z digest=sha256:f59821f7df7dc7a8ef6cb6f9c5246c4ae2e2f2def74b073cf3852b97fb3a1030

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:04.575468Z digest=sha256:42254b4caa71eaea7b5b1ff23164b055854d1b9a59732d636613f5be24770d03

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:04.718039Z digest=sha256:2c84feb6b33d57508a75552357c3e743e222a205b4ef8c2cfd8cdeb11c03d274

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:04.898522Z digest=sha256:a537c6c8f9f44e31c150f7271adfd39bd5472fce9e8d47dde3e5bb9b31c7a136

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:04.974166Z digest=sha256:a165b2fc952572284779493bc875e8cc9eda8d6f7a1ad60e06295f59d2db594f

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.094039Z digest=sha256:b5fe8b977d5c356afb8c83e22c2b4980942ae3d8115988d61adb062fead72065

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.218644Z digest=sha256:823ee94776a17bf08594e59cc19328f4457b55ae76691c795739ad9f6792298c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.387611Z digest=sha256:ad5fc8c8ec272472cdad7fe697ec483bddae37f93c9b4d91295ef05ec75b8723

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.521073Z digest=sha256:2f0924a3dce7c5726dc7126eda045eef76c787e9686659b451b1c7451b371ca6

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.648401Z digest=sha256:bc812a8865738645ff0fc6925f1a306f14143c9dfba981b6d6b30f453bb62084

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:05.846778Z digest=sha256:62dd10e96385601acf456df3c661d85d54cdbad5cb79bb5209a6465ba83868ab

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.057813Z digest=sha256:d89e69011f46248d5f4a1bb5f620abc6406bf2b6fb4be7a47473a6e3701dc92b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.173724Z digest=sha256:b51e5d46bbba3a5f1fcac75672c965de18053e35a24d841218fe1c309586c9bd

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.293534Z digest=sha256:ceeefc146e711586aaac098c0a71e2efef411280d130656d6f2aff2f7df52446

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.462436Z digest=sha256:a67d3e511c5ffc809168bebc68eaf38df595d455032144b7d3bc0c64a45e14b2

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.605423Z digest=sha256:0d99ee3edf0602e4fa366591e225a252c9954c311db57795bfa8659bd96a3b89

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.744498Z digest=sha256:6cda26b4f81a364bb7cb421b57d7d21b19f551d995c2344fb36a79b1b022cb38

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:06.928443Z digest=sha256:b001ebababa1cc573d202a4ecb415062561c709ef13f2cd07c31baa6f6fc2448

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

Resolution
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no resolver link, observed 2026-08-07T13:10:07.072452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:07.072452Z digest=sha256:93c8daec31370d0bdf5cd80d5e272a1307b3ba8b7620e27b18a2be04be6689d9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.202405Z digest=sha256:2aa125f68453fba5217ba8931207cfc6e0214ef7730a416850beefc9bfe8e7be

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.335320Z digest=sha256:437d1012caec844b516ad658357f73591823afa1158ac8f9c1db324ca17af79e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.486743Z digest=sha256:023ad0fdfe56eff6dc9237824f248504992bd4b090833284280e6056c8ba2695

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.663602Z digest=sha256:ddb5995316998f55970bdb4be6464c9a168348692cb6d6c5d38e3ab7dd1fa2d6

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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.830359Z digest=sha256:97daaf410b3a9f32e0a70c825e8b56ed0d158570bca6926789ab8761148089fc

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:07.935523Z digest=sha256:50a14f595794aa25cc67ad2331c93e9d533df918fa998eba5ab39a3a1334439b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:08.060825Z digest=sha256:2e7fe6a0c4dd6a2aa02cced276f8477db85e78a2eea61f8bd43bc6c06efd49b1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:08.282593Z digest=sha256:d2a814a910f4e37e443f6b3fd317366ec5cb7931e3a2700a08ea995b8e0fa0f6

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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:08.400143Z digest=sha256:a406120fc5ece8a16e1fa7dbd9471dccf2a43dfc58889300c9a43a4b9c47784d

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:08.563542Z digest=sha256:08adfa18f95c0effa063bcf18927856e490e416a519f42604c3a1798459e936a

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:08.737225Z digest=sha256:e6b44538b1e76ac415f00831eae1e8a45a7bf0ef7ab2476d9d4812df0f4dd1e8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:08.896020Z digest=sha256:6e75999bfb25d64f23596845336a187e5758e7e0a10ac4126ad8eb889d0feef8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:09.084874Z digest=sha256:9a34859b19879c687215309e6fb3bb99218627c12915af789082686dbf5d7a3b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:09.261308Z digest=sha256:b18dd872545e9852927f5226aae96ae6acde0f6114cd771f0e607bae8f44d394

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

Resolution
unresolved
no resolver link, observed 2026-08-07T13:10:09.455799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:09.455799Z digest=sha256:69efd6171410fafe4f59a0c093a48e1bdfaca38fcd18d7dfffa0d957309cc58d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:09.639043Z digest=sha256:0d490fc41e47b9949032a356c61891bf84513bee26bd31a6839634e3c109f6a5

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:09.868806Z digest=sha256:633891d76b02b18cce4222a1ad29bf5f8f69afc57bf68705031b7956b93a4df4

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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:10.023098Z digest=sha256:8a55a6c286278e388625ee0151e3a94a39226cd618e8fd489f714df64bd33831

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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:10.154755Z digest=sha256:39968e7bb45eb85f8a524f85744a055c9ab5304a85fdc4d94bf6a38d8272341c

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:10.316669Z digest=sha256:a832fa130393af7a5f3e57d5a3b61c4477bd2b2e909b5c8cfce80a6a26eca242

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:10.411364Z digest=sha256:c3ae8bb43e1d0c56e898b07fc58acfc6318575f02f5c75dd158e0c99a8dde738

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:10.548879Z digest=sha256:c66bb4f42b391d34105fbaeddda70ab3d32d3a2ac493891da390117a2700cc87

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.

source=pdf_text observed=2026-08-07T13:10:10.711035Z digest=sha256:5a516e1bcad9ea057a82455a5bc69da2fa8b7ea1b6a5daeab85951ff64a60142

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.

source=pdf_text observed=2026-08-07T13:10:10.917149Z digest=sha256:bf40af4f7bfcf674d35ba2cc5121d8d2413120c22d4e83042431a080f5ccfc0d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:11.082351Z digest=sha256:731f50a925ef23f56adcd110a33094bfcd45629631af36379c99845b9991bd23

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:11.239273Z digest=sha256:a2175874f459caa74cf96f97e33660461f6d080d82586f5c5cb9ea8d03710f02

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:11.437478Z digest=sha256:90b3bf27ef485db0707bd18cd9309372b94d19aa4fd3384cb62414d9ff8832f4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:10:11.570195Z digest=sha256:7082504eecf748e321d5c1204efa11d531af670c3c3b9b8b4db701e11711aee6

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

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:10:11.740399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:11.740399Z digest=sha256:8bab940d05463e7abbe3e49be137ab157d2fa454cf0b4ff1d52380bdfdccde18

Pith citing papers

No inbound Pith citation observations are available.