TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization | Paper Citation Record

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This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Wan: Open and Advanced Large-Scale Video Generative Models

Reference 1

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This paper cites Open-Sora: Democratizing Efficient Video Production for All.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Open-Sora: Democratizing Efficient Video Production for All

Reference 2

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This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , year=.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , year=

Reference 3

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of the 36th International Conference on Neural Information Processing Systems , articleno =

Reference 4

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This paper cites Grounded copilot: How programmers interact with code-generating models.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Grounded copilot: How programmers interact with code-generating models

Reference 5

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2024 , howpublished=

Reference 6

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2024 , eprint=

Reference 7

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization European Conference on Computer Vision (ECCV) , pages=

Reference 8

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2025 , howpublished=

Reference 9

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This paper cites Fast On-Device LLM Inference with NPUs , booktitle =.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Fast On-Device LLM Inference with NPUs , booktitle =

Reference 10

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Unresolved cited work

Reference 11

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization European Conference on Computer Vision (ECCV) , pages=

Reference 12

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year=

Reference 13

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Advances in Neural Information Processing Systems (NeurIPS) , year=

Reference 14

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , year =

Reference 15

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , volume =

Reference 16

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Neural Information Processing Systems (NeurIPS) , pages=

Reference 17

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This paper cites CLIPS core: A Reference-free Evaluation Metric for Image Captioning.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization CLIPS core: A Reference-free Evaluation Metric for Image Captioning

Reference 18

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Machine Learning (ICML) , pages=

Reference 19

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization European conference on computer vision (ECCV) , pages=

Reference 20

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization and Shechtman, Eli and Wang, Oliver , booktitle=

Reference 21

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This paper cites ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation

Reference 22

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF International Conference on Computer Vision (ICCV) , pages=

Reference 23

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization GODIVA: Generating Open-DomaIn Videos from nAtural Descriptions

Reference 24

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Structure and Content-Guided Video Synthesis with Diffusion Models , year=

Reference 25

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 26

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=

Reference 27

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=

Reference 28

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 29

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

Reference 30

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE Trans

Reference 31

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Scaling rectified flow transformers for high-resolution image synthesis , year =

Reference 32

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization and Mahendran, Aravindh and Yu, Fisher and Oliver, Avital and Huot, Fantine and Bastings, Jasmijn and Collier, Mark Patrick and Gritsenko, Alexey A

Reference 33

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Improved Video VAE for Latent Video Diffusion Model , year=

Reference 34

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Qwen2.5: A Party of Foundation Models , url =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Language Model Beats Diffusion - Tokenizer is key to visual generation , volume =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Latte: Latent Diffusion Transformer for Video Generation

Reference 37

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Scalable Diffusion Models with Transformers , year=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation , year=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=

Reference 40

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Synthetic Video Enhances Physical Fidelity in Video Synthesis

Reference 41

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 19th USENIX Symposium on Operating Systems Design and Implementation (OSDI 25) , year=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration , volume =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Nvidia blackwell architecture technical brief , url =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2024 , month =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of Machine Learning and Systems (MLSys) , year =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of Machine Learning and Systems (MLSys) , year=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization and Li, Bo and Cameron, Pashmina and Jaggi, Martin and Alistarh, Dan and Hoefler, Torsten and Hensman, James , title =

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Svirschevski and Vage Egiazarian and Denis Kuznedelev and Elias Frantar and Saleh Ashkboos and Alexander Borzunov and Torsten Hoefler and Dan Alistarh , booktitle=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Machine Learning (ICML) , pages=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Scaling Vision Transformers , year=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF international conference on computer vision (CVPR) , pages=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) , pages=

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2020 , booktitle =

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Reference 57

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Reference 58

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year =

Reference 60

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Observation 0223d693-67c4-496a-b8dc-0c5e962cdf14 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 61

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Observation 5627103e-884f-4883-8fab-8392427edd3e · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of the 40th International Conference on Machine Learning (ICML) , pages =

Reference 62

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Observation 8e532454-8546-41e4-aadd-ab025b49d100 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) , volume=

Reference 63

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Observation 4bf8693e-41c9-4840-b9ca-83113b472493 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF conference on computer vision and pattern recognition (CVPR) , pages=

Reference 64

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Observation 8cf11859-6939-4b49-9410-c14887f5d584 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2023 , booktitle =

Reference 65

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Observation 3f4147ef-2270-4909-a30d-62f812bc604a · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , year=

Reference 66

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Observation 4193eb39-0393-401b-9ff5-929ee7697d39 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Cache Me if You Can: Accelerating Diffusion Models through Block Caching , year=

Reference 67

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Observation 4e2e3677-2cbf-4343-ae54-5607eebe767d · outbound

This paper cites and Kaiser,.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization and Kaiser,

Reference 68

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Observation 13f5f476-2f76-4239-ad8d-254cb7ca6ead · outbound

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Reference 69

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Observation 3cb0ef35-9ca6-45fa-9632-d9a643d66168 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 70

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Observation 717f842e-0bfd-4997-960f-621b69600721 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year=

Reference 71

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Observation 274e4781-db38-4d51-9de9-071f045725f2 · outbound

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Reference 72

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Observation dd0c2344-ea03-4149-ac38-723859c76b31 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year=

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation 2b48d05b-7825-47ce-96ba-4990d77db864 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation f39c7e0b-a33e-4b36-80fe-34ffd79bf228 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization The Llama 3 Herd of Models

Reference 75

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Observation 75e1d110-e35a-476a-ad93-f7aabe6662cf · outbound

This paper cites Qwen3 Technical Report.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Qwen3 Technical Report

Reference 76

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Observation fdf7abbb-ca51-4339-a96d-308c9d045d26 · outbound

This paper cites GPT-4 Technical Report.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization GPT-4 Technical Report

Reference 77

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T00:56:24.874976Z

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Observation b5288b24-6904-4f71-90a0-0a0f4d47b49f · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Gemini: A Family of Highly Capable Multimodal Models

Reference 78

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T00:56:24.906883Z

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Observation 954e21b2-8646-4a03-8041-068842e25c6a · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Nature Medicine , year =

Reference 79

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Observation fee6b366-7aff-4072-9b35-b17bac34a44e · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Machine Learning (ICML) , year =

Reference 80

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Symposium on Operating Systems Principles (SOSP) , pages=

Reference 81

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Observation 8c269f74-400d-418e-910f-7fa6c38e48eb · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2024 , booktitle =

Reference 82

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Observation 26e99727-3048-4326-a68c-815289d19e5e · outbound

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Reference 83

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Observation fb923b0d-ed24-4bb8-aad4-a156edcca43e · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Mobile Computing and Networking (MobiCom) , year=

Reference 84

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Machine Learning (ICML) , pages=

Reference 85

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation 848332cd-c434-4e9b-9fc7-5196ee22a439 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2025 , booktitle =

Reference 86

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Observation f1698d78-7272-4684-a23d-23147f0e316d · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization LRQ uant: Learnable and Robust Post-Training Quantization for Large Language Models

Reference 87

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year =

Reference 88

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Reference 89

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Observation cb501c8e-5c3e-4e5b-be4c-aed77a39b9b7 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization International Conference on Learning Representations (ICLR) , year=

Reference 90

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Proceedings of the AAAI conference on artificial intelligence (AAAI) , volume=

Reference 91

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Observation 444d4d10-f9e6-4f4e-ac2c-6ccc9421b5e1 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 92

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Observation b4d4eb6e-d8d7-4786-9822-a7c89ac54e9c · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization H ella S wag: Can a Machine Really Finish Your Sentence?

Reference 93

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation d18952ae-13dc-409a-b050-c281458c70e7 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 94

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation b9b18822-2e7e-42c0-b27b-199d2a6e4ba0 · outbound

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Reference 95

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation d4ab0949-1391-4e49-8e76-b7ca6eb74d8c · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization DeepSeek-V3 Technical Report

Reference 96

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T00:56:24.890149Z

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Observation d41fa7b2-51ec-4e23-9521-e19d80faedd3 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform

Reference 97

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Observation e0476a07-02cd-4230-938b-1f413afda189 · outbound

This paper cites 2024 , booktitle =.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization 2024 , booktitle =

Reference 98

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Observation 05ad2148-6f45-44a9-bc59-f77fc1f5caa0 · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Unresolved cited work

Reference 99

Resolution: unresolved; no resolver link, observed 2026-06-28T13:07:53.001390Z

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Observation c504d84a-0b2d-4614-a750-898e16cfb00e · outbound

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TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation

Reference 100

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T00:56:24.899516Z

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Coverage vector

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Outbound references

Pith citing papers