On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention | Paper Citation Record

Observation 5bfda6f3-306d-41fd-931b-8187ceac2d05 · outbound

This paper cites write newline.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention write newline

Reference 1

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Observation f13a33ab-b5eb-4658-b2f7-6f3d8873d112 · outbound

This paper cites https://huggingface.co/blog/bamba.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention https://huggingface.co/blog/bamba

Reference 2

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Observation 0b7d6472-f4b2-4a0e-a991-5a5a52832d11 · outbound

This paper cites nvidia.com.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention nvidia.com

Reference 3

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Observation b283f60b-528c-487d-937c-6b79e056f232 · outbound

This paper cites Y., Rajbhandari, S., Awan, A.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Y., Rajbhandari, S., Awan, A

Reference 4

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Observation 98ce186c-6273-4abe-aaad-b75d1ef8b7a1 · outbound

This paper cites E., and Pedram, M.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention E., and Pedram, M

Reference 5

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Observation 5273c4d9-aed8-4fc5-9d84-7a4e9a747c66 · outbound

This paper cites L ong B ench: A bilingual, multitask benchmark for long context understanding.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention L ong B ench: A bilingual, multitask benchmark for long context understanding

Reference 6

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Observation b4b23c6f-a9c4-450c-af41-b565de419c9f · outbound

This paper cites Longformer: The Long-Document Transformer.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Longformer: The Long-Document Transformer

Reference 7

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Observation 3b11432c-7289-4214-a0e8-0356dc373cd5 · outbound

This paper cites DeciMamba: Exploring the Length Extrapolation Potential of Mamba.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention DeciMamba: Exploring the Length Extrapolation Potential of Mamba

Reference 8

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Observation eaa20003-4262-4252-8800-37325f79b0d9 · outbound

This paper cites Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models

Reference 9

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Observation c038ba8e-116a-48c4-9d24-081a163a488a · outbound

This paper cites Read-me: Refactorizing llms as router-decoupled mixture of experts with system co-design.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Read-me: Refactorizing llms as router-decoupled mixture of experts with system co-design

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:59.780840Z

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Observation 07d2a5a3-58fd-4863-bd67-88bfea0b78d1 · outbound

This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Reference 11

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Observation 1c3c1ef5-6963-4f2d-be24-b2e6f1caf26a · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Generating Long Sequences with Sparse Transformers

Reference 12

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Observation 3f981207-6675-465c-bddf-5865bbf9af51 · outbound

This paper cites Rethinking Attention with Performers.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Rethinking Attention with Performers

Reference 13

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Observation caa8a0d6-4443-4244-be32-5541b466d2b0 · outbound

This paper cites B., Bierbaum, M., O'Keeffe, K.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention B., Bierbaum, M., O'Keeffe, K

Reference 14

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Observation dd369b7c-a24e-4e77-9095-027a32d5b3af · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 15

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Observation 7656668f-69cb-4452-a0d4-fd5e041f863f · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.481739Z

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Observation 55ab2dfb-5b33-4648-897b-1a4f4fa7ad5f · outbound

This paper cites Fast Inference of Mixture-of-Experts Language Models with Offloading.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Fast Inference of Mixture-of-Experts Language Models with Offloading

Reference 17

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Observation 131ca01e-8ce2-4a38-a120-994baca3c13d · outbound

This paper cites Stack exchange data dump, 2024.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Stack exchange data dump, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:59.265908Z

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Observation 64f49872-e4ba-4ea9-81e7-b1f0040dceb4 · outbound

This paper cites Wikimedia downloads.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Wikimedia downloads

Reference 19

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Observation 4e870e7c-e10d-49bc-a9a6-3d37f9ae665a · outbound

This paper cites and Alistarh, D.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention and Alistarh, D

Reference 20

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Observation 9b73c7ec-2a49-4a10-abcc-e60a0b7ec9ee · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 21

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Observation f2f1a551-1433-40be-83a9-31b56dcc05cc · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 22

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Observation 00105b00-2053-4aee-8bf6-8b37ef7c0782 · outbound

This paper cites Zamba: A Compact 7B SSM Hybrid Model.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Zamba: A Compact 7B SSM Hybrid Model

Reference 23

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Observation b572fc40-30bf-400c-89ce-597be1886fbf · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 24

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Observation 4df2d4b4-e48d-4630-a050-d2a0ad4d3c48 · outbound

This paper cites N V I D I A H 100 T ensor C ore G P U D atasheet --- resources.nvidia.com.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention N V I D I A H 100 T ensor C ore G P U D atasheet --- resources.nvidia.com

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:58.550360Z

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Observation 24fec936-f6af-457d-afa1-96c547d714c2 · outbound

This paper cites M., Kocisky, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., and Blunsom, P.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention M., Kocisky, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., and Blunsom, P

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:58.326820Z

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Observation 2af91c23-f9c4-4c00-adfb-ca5d731a8b56 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Distilling the Knowledge in a Neural Network

Reference 27

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Observation 474fa1c2-123c-40e7-83e2-405f0ef97487 · outbound

This paper cites What does bert learn about the structure of language? In ACL 2019-57th Annual Meeting of the Association for Computational Linguistics, 2019.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention What does bert learn about the structure of language? In ACL 2019-57th Annual Meeting of the Association for Computational Linguistics, 2019

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:58.092789Z

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Observation 9c07b291-0a01-4b32-97a8-91d25c9f1e2f · outbound

This paper cites Finetuning Pretrained Transformers into RNNs.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Finetuning Pretrained Transformers into RNNs

Reference 29

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Observation f4fd3083-54f4-497e-9cb9-71726f172800 · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 30

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Observation b7bd5cda-0fe8-4210-9584-91b6f27db0bc · outbound

This paper cites MatFormer: Nested Transformer for Elastic Inference.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention MatFormer: Nested Transformer for Elastic Inference

Reference 31

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Observation 486207a5-8545-41c4-a53b-f6594aeacc91 · outbound

This paper cites H., Gonzalez, J., Zhang, H., and Stoica, I.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention H., Gonzalez, J., Zhang, H., and Stoica, I

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:57.806373Z

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Observation f8dbd3fc-40c9-40ed-9b15-0bc4e9df16b3 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 33

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Observation b52c1bab-5b63-4813-a562-1d957af6f787 · outbound

This paper cites Fast inference from transformers via speculative decoding.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Fast inference from transformers via speculative decoding

Reference 34

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Observation 2a74723d-51c5-4d7a-823a-b6da73242916 · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Textbooks Are All You Need II: phi-1.5 technical report

Reference 35

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Observation bf0c30b2-e33f-4a74-b80c-251072379c79 · outbound

This paper cites SnapKV: LLM Knows What You are Looking for Before Generation.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention SnapKV: LLM Knows What You are Looking for Before Generation

Reference 36

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Observation ee832730-6ad7-4ea4-9774-9acec88298a3 · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Jamba: A Hybrid Transformer-Mamba Language Model

Reference 37

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Observation 0cd404f9-d719-4b20-970b-990fd9feea19 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Rouge: A package for automatic evaluation of summaries

Reference 38

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Observation 9eeb5ed2-3dd4-41f4-a0bd-08b52facb7b3 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Awq: Activation-aware weight quantization for on-device llm compression and acceleration

Reference 39

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Observation 02c42fcb-6b4e-4151-b79c-b91655505b04 · outbound

This paper cites Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 40

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Observation 21557610-a2cf-4868-8bde-b8463e0986e7 · outbound

This paper cites MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Reference 41

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Observation 8b5a5c8a-968c-454b-8ef8-e040a5dc07d0 · outbound

This paper cites Decoupled Weight Decay Regularization.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Decoupled Weight Decay Regularization

Reference 42

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Observation 22cd5a87-b673-442a-8b2d-2bf833df611b · outbound

This paper cites Llm-pruner: On the structural pruning of large language models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Llm-pruner: On the structural pruning of large language models

Reference 43

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Observation 0b665a0f-8f6e-4ac9-9596-5380efcd79bd · outbound

This paper cites Linearizing Large Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Linearizing Large Language Models

Reference 44

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Observation 12c7d4d8-c4d6-4ec6-afda-aebf182d97fa · outbound

This paper cites Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Reference 45

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Observation f818956f-faa5-4580-8650-0a35e4044183 · outbound

This paper cites Splitwise: Efficient generative llm inference using phase splitting.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Splitwise: Efficient generative llm inference using phase splitting

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:57.439523Z

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Observation 1a8c189a-0b4c-4e2b-a3ff-5b961b0940fc · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention RWKV: Reinventing RNNs for the Transformer Era

Reference 47

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Observation f69b21ac-6d7e-4951-9be5-a155f70a92a3 · outbound

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On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Unresolved cited work

Reference 48

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Observation c20b2571-24fe-4f0a-8c43-4f5d0a729026 · outbound

This paper cites Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling

Reference 49

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Observation 5667ba96-4ed2-4d78-a3d6-b58cc4f15d35 · outbound

This paper cites Optimizing transformer inference with selective distillation: Layerwise conversion to linear attention.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Optimizing transformer inference with selective distillation: Layerwise conversion to linear attention

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:57.163885Z

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Observation 7438f84c-e48b-4583-94ed-4f2777083c0c · outbound

This paper cites Get To The Point: Summarization with Pointer-Generator Networks.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Get To The Point: Summarization with Pointer-Generator Networks

Reference 51

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Observation 19a7c27f-c1ea-422c-aba3-76d047304e95 · outbound

This paper cites SlimPajama-DC: Understanding Data Combinations for LLM Training.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention SlimPajama-DC: Understanding Data Combinations for LLM Training

Reference 52

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Observation db541a76-d744-4267-bcb4-3b42e9e53540 · outbound

This paper cites TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

Reference 53

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Observation c80eeb53-48e5-42f8-98f1-e8219f002748 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention A Simple and Effective Pruning Approach for Large Language Models

Reference 54

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Observation 4f864534-554c-49e0-b005-f2559d13cd72 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Retentive Network: A Successor to Transformer for Large Language Models

Reference 55

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Observation 5ebb6325-398b-4bcd-8eb1-b762d92e1674 · outbound

This paper cites Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference

Reference 56

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Observation cb530a10-3b22-4f0c-9a4e-a4d1d398d34d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention LLaMA: Open and Efficient Foundation Language Models

Reference 57

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Observation 9eae3fa5-0e4f-4652-baa6-55672d7c2c02 · outbound

This paper cites Attention is all you need.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Attention is all you need

Reference 58

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Observation 4bd7ea9a-c26c-40db-974c-73cf8af22a5c · outbound

This paper cites An Empirical Study of Mamba-based Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention An Empirical Study of Mamba-based Language Models

Reference 59

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Observation fd2e9bb5-50df-4e33-b77f-02ae198cc928 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 60

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Observation c37d3d81-be26-491d-8cf4-c007a1195ab3 · outbound

This paper cites The Mamba in the Llama: Distilling and Accelerating Hybrid Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention The Mamba in the Llama: Distilling and Accelerating Hybrid Models

Reference 61

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Observation 78136a9d-755a-4e54-a2d9-3a851978ff3c · outbound

This paper cites Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing

Reference 62

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Observation ac56f147-bab8-4dec-8882-d00e29c9e3ba · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Linformer: Self-Attention with Linear Complexity

Reference 63

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Observation bd53dc6b-d00c-4058-bedf-aa578be4126f · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.748448Z

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Observation f53d8580-e9a3-47d3-8a15-896ccef73530 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Efficient Streaming Language Models with Attention Sinks

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.815383Z

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Observation 508c89cd-b939-4ffb-8522-a5a5eb53a68b · outbound

This paper cites Gated Linear Attention Transformers with Hardware-Efficient Training.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Gated Linear Attention Transformers with Hardware-Efficient Training

Reference 66

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Observation f5a99ef4-a68c-4e5d-a02a-a37257d44035 · outbound

This paper cites FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:55.007481Z

Source-reported events for the cited work

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Observation 806fe173-a090-432d-bc7b-b63718448c40 · outbound

This paper cites S., Kim, G.-W., Kim, S., and Chun, B.-G.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention S., Kim, G.-W., Kim, S., and Chun, B.-G

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:58:56.922471Z

Source-reported events for the cited work

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Observation 9ffaab65-25e7-401b-b739-253b974d5ed5 · outbound

This paper cites A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:55.348157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c2ba22a-125f-4c20-b045-c6e43cb22b8f · outbound

This paper cites LoLCATs: On Low-Rank Linearizing of Large Language Models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention LoLCATs: On Low-Rank Linearizing of Large Language Models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:55.594059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09d1b7ac-3019-4ad9-81a3-0dd013c889d8 · outbound

This paper cites The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:55.827537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397da5de-50cc-4ae0-8606-ec5277bca783 · outbound

This paper cites H2o: Heavy-hitter oracle for efficient generative inference of large language models.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention H2o: Heavy-hitter oracle for efficient generative inference of large language models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:56.004667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05c3c4a2-b8a6-463f-aa81-d4c5e9be40ae · outbound

This paper cites P., Zhang, H., Gonzalez, J.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention P., Zhang, H., Gonzalez, J

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:56.185517Z

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