Paper Citation Record · LEDGER

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model

As of 13 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.24007.

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

pith.paper-citation-record.v1
2505.24007 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:41:00.935085Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

45 of 45 outbound references displayed

verified exact7
verified fuzzy1
unresolved33
parse uncertain0
malformed identifier3
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a5846db8-7a21-478d-bd71-0d8ea749fda5 · outbound

This paper cites Large Language Models Meet Computer Vision: A Brief Survey.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Large Language Models Meet Computer Vision: A Brief Survey

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:41:02.793428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 251261e7-b271-4c35-bb4b-469ee052b063 · outbound

This paper cites Neural Computing and Applications 37(4), 1973–1997 (2025) https://doi.org/10.1007/s00521-024-10827-6.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Neural Computing and Applications 37(4), 1973–1997 (2025) https://doi.org/10.1007/s00521-024-10827-6

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:56.294964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ac390b1-69d9-40b1-928f-22f61521a3cc · outbound

This paper cites In: 2024 27th International Conference on Computer and Information Technology (ICCIT), pp.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: 2024 27th International Conference on Computer and Information Technology (ICCIT), pp

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:56.356073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 243c1c26-057b-4dd5-ae2a-9cb1d7b616e1 · outbound

This paper cites Neural Computing and Applications (2025) https://doi.org/10.1007/ s00521-024-10495-6.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Neural Computing and Applications (2025) https://doi.org/10.1007/ s00521-024-10495-6

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:41:04.534859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3ace651d-25bc-42b4-a803-321a022b1c85 · outbound

This paper cites In: Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pp.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pp

Reference 5

Resolution: verified exact; doi, observed 2026-08-07T12:41:02.594651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7a670189-2eb5-4f15-a4fb-0d891c7faa57 · outbound

This paper cites Natural Language Processing Journal 7, 100079 (2024) https: //doi.org/10.1016/j.nlp.2024.100079.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Natural Language Processing Journal 7, 100079 (2024) https: //doi.org/10.1016/j.nlp.2024.100079

Reference 6

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T12:41:03.771280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7512a4f4-d9a1-4cc2-ab47-0299bb71815f · outbound

This paper cites In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp

Reference 7

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:41:04.279671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f68a974-2e4a-4bc9-991d-c025d913b1af · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 46(8), 5625–5644 (2024) https://doi.org/10.1109/TPAMI.2024.3369699 18.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model IEEE Transactions on Pattern Analysis and Machine Intelligence 46(8), 5625–5644 (2024) https://doi.org/10.1109/TPAMI.2024.3369699 18

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:56.736341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b3278f-bb94-47fb-9f7e-a5f0c175563f · outbound

This paper cites In: 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:56.867713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c693f11c-ba13-4b5e-8fbb-38ed28f9d3d5 · outbound

This paper cites Neural Computing and Applications 36(33), 20849–20861 (2024) https://doi.org/10.1007/s00521-024-10310-2.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Neural Computing and Applications 36(33), 20849–20861 (2024) https://doi.org/10.1007/s00521-024-10310-2

Reference 10

Resolution: verified exact; doi, observed 2026-08-07T12:41:02.379643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 964e48c8-3227-402e-9bf1-404735c696fa · outbound

This paper cites ACM Transactions on Information Systems 43(2), 1–55 (2025) https://doi.org/10.1145/3703155.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model ACM Transactions on Information Systems 43(2), 1–55 (2025) https://doi.org/10.1145/3703155

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:57.134997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3660bffe-a860-46d9-8b63-2f13919212e5 · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:57.268736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6763a4c0-e56b-4ab5-a684-6fba44ac812f · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:57.368955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d52194f0-3366-4b28-8c97-dafd754a9aa1 · outbound

This paper cites https://cdn.openai.com/papers/ GPTV System Card.pdf.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model https://cdn.openai.com/papers/ GPTV System Card.pdf

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:41:04.124117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a3fb02c4-1287-4b5d-a734-4c7c3bfe0f13 · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:57.592968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 862b44a8-62ee-49d1-b434-f352787d9f27 · outbound

This paper cites Visual Hallucinations of Multi-modal Large Language Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Visual Hallucinations of Multi-modal Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:57.776021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 359af40f-55f2-4189-a8e5-adc2f19f4a93 · outbound

This paper cites Neural Computing and Applications (2025) https: //doi.org/10.1007/s00521-025-11229-y.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Neural Computing and Applications (2025) https: //doi.org/10.1007/s00521-025-11229-y

Reference 17

Resolution: verified exact; doi, observed 2026-08-07T12:41:02.031620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eeefadf2-cac0-4f77-877e-2bbe79f734ec · outbound

This paper cites Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.104064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1425827c-cdfc-46a2-b052-c93e6219074f · outbound

This paper cites Neural Computing and 19 Applications (2025) https://doi.org/10.1007/s00521-024-10895-8.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Neural Computing and 19 Applications (2025) https://doi.org/10.1007/s00521-024-10895-8

Reference 19

Resolution: verified exact; doi, observed 2026-08-07T12:41:01.833515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e945f82f-3692-4d0f-a26f-b062d481658e · outbound

This paper cites Detecting and Evaluating Medical Hallucinations in Large Vision Language Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.390282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d48a18e-b26f-466c-814c-9f41d170f2c0 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Hallucination of Multimodal Large Language Models: A Survey

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.547958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58875b92-2d6f-4d65-b8d5-82a3ba694024 · outbound

This paper cites CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.682028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41bcaaba-f3ba-46d8-bec9-fbdd8b83738d · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Evaluating Object Hallucination in Large Vision-Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.836392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6872bd60-f2e8-4c26-8daf-3792654f3b93 · outbound

This paper cites Visual Instruction Tuning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Visual Instruction Tuning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.909680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad7278ce-b8e9-4fc0-b928-a74fcfd77ee9 · outbound

This paper cites AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:58.968730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e796555-5004-4122-aed7-ad1797ff95bf · outbound

This paper cites https://doi.org/10.1109/CVPR52733.2024.01230.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model https://doi.org/10.1109/CVPR52733.2024.01230

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.057403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2af4382f-70d7-45af-a622-cb1375061370 · outbound

This paper cites Object Hallucination in Image Captioning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Object Hallucination in Image Captioning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.118464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a74ec7fb-aaca-4dbd-9efa-2e0eb2d096e4 · outbound

This paper cites Visual Instruction Tuning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Visual Instruction Tuning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.202797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 525724e9-67f9-4f45-b474-b64e6b4a0775 · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.276089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008afc84-f0ff-4cd3-9b62-13d7aa902acf · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.350199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f974fdf9-da18-43a7-9d6f-e7adfad9b256 · outbound

This paper cites Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.418262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dcbec0e-33a8-4869-bbab-1419a0e70079 · outbound

This paper cites Visual Instruction Tuning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Visual Instruction Tuning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.497050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dc94f1a-9b52-4f35-995b-4e5a42951b2a · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.657207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4f3f71a-54bc-4b65-acef-f8bb1c8e0041 · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:59.884885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8898939a-b9f7-47d9-8342-ad36587b6e31 · outbound

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

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 37

Resolution: malformed identifier; no resolver link, observed 2026-08-07T12:41:00.011918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7ba7add-402f-46b0-8973-0a7fd14a29a9 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.088984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 473c8ee1-3e15-4275-b381-996af429d938 · outbound

This paper cites arXiv preprint arXiv:2503.10602 (2025) https: //doi.org/10.48550/arXiv.2503.10602.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model arXiv preprint arXiv:2503.10602 (2025) https: //doi.org/10.48550/arXiv.2503.10602

Reference 39

Resolution: verified exact; doi, observed 2026-08-07T12:41:01.373295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8a9d247e-884c-4bea-a11f-76a279545091 · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Improved Baselines with Visual Instruction Tuning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.211781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b19066f8-044c-4b14-90ad-ee316cc24946 · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.303458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6ce1d0e-33e8-4244-97ba-91b9add0c013 · outbound

This paper cites HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.398895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7a1c40a-a0c8-4e8b-b8a4-1fbc8161ccff · outbound

This paper cites Acoustics, Speech and Signal Processing, IEEE Transactions on 27, 13–18 (1979) https: //doi.org/10.1109/TASSP.1979.1163188.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Acoustics, Speech and Signal Processing, IEEE Transactions on 27, 13–18 (1979) https: //doi.org/10.1109/TASSP.1979.1163188

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.521223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc214bc1-4142-46e3-bd3b-a1c6675b8943 · outbound

This paper cites Prentice- Hall, Inc., USA (2006).

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model Prentice- Hall, Inc., USA (2006)

Reference 44

Resolution: verified exact; raw_fallback, observed 2026-08-07T12:41:03.083893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a133b97-3d01-4a6d-af50-7926e5aee6da · outbound

This paper cites In: Jurafsky, D., Chai, J., Schluter, N., Tetreault, J.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: Jurafsky, D., Chai, J., Schluter, N., Tetreault, J

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.733910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d36e74e-88dc-4ae6-88ce-daef072ff68a · outbound

This paper cites In: Walker, M., Ji, H., Stent, A.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model In: Walker, M., Ji, H., Stent, A

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.823710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76158028-c7d8-4caf-a3c0-1f8050e03bf0 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T12:41:00.935085Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.