HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling | Paper Citation Record

Observation 9d5d8299-25da-4e08-acb8-9b1a4662ef11 · outbound

This paper cites A sequence-based global map of regulatory activity for deciphering human genetics.Nature genetics, 54(7):940–949, 2022.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling A sequence-based global map of regulatory activity for deciphering human genetics.Nature genetics, 54(7):940–949, 2022

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:50.616706Z

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Observation 4f9b8caf-0a94-47e7-8437-99bd66c2e812 · outbound

This paper cites Artificial intelligence-guided strategies for next-generation biological sequence design.National Science Review, 11(11):nwae343, 2024.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Artificial intelligence-guided strategies for next-generation biological sequence design.National Science Review, 11(11):nwae343, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:50.459071Z

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Observation 23d5bf8b-6367-4ddc-97f6-1214de94ff09 · outbound

This paper cites Dnabert: pre-trained bidirectional encoder representations from transformers model for dna-language in genome.Bioinformatics, 37(15):2112–2120, 2021.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Dnabert: pre-trained bidirectional encoder representations from transformers model for dna-language in genome.Bioinformatics, 37(15):2112–2120, 2021

Reference 3

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Observation 23d35700-a73e-4104-8252-f38eb3b3bf17 · outbound

This paper cites DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome

Reference 4

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Observation 80b95b1b-6262-4596-9f92-b91f34903f1b · outbound

This paper cites Nucleotide transformer: building and evaluating robust foundation models for human genomics.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Nucleotide transformer: building and evaluating robust foundation models for human genomics

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:50.293370Z

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Observation efa0cb38-4a45-4925-adb5-91b1bf76f500 · outbound

This paper cites Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution.Advances in neural information processing systems, 36:43177–43201, 2023.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution.Advances in neural information processing systems, 36:43177–43201, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:50.144203Z

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Observation a2b3ff30-67be-4237-b12d-693f7afd5f84 · outbound

This paper cites Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling

Reference 7

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Observation efdf888f-b8e3-4ec3-9d9c-73061b260054 · outbound

This paper cites an unresolved cited work.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:53:49.974467Z

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Observation a5c0ba5c-857c-4bb3-a072-9da3e9a6e7ef · outbound

This paper cites Predicting rna-seq coverage from dna sequence as a unifying model of gene regulation.Nature Genetics, pages 1–13, 2025.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Predicting rna-seq coverage from dna sequence as a unifying model of gene regulation.Nature Genetics, pages 1–13, 2025

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:49.806181Z

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Observation 0386a878-954f-4cf9-93d5-6959bef397b7 · outbound

This paper cites Do we really have to filter out random noise in pre-training data for language models?.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Do we really have to filter out random noise in pre-training data for language models?

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:41.436077Z

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Observation dbaf88b1-9f76-4309-9d8c-307904d44fce · outbound

This paper cites Genomic language models could transform medicine but not yet.npj Digital Medicine, 8(1):212, 2025.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Genomic language models could transform medicine but not yet.npj Digital Medicine, 8(1):212, 2025

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:49.619596Z

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Observation df3bd301-801c-4399-bc1f-359bdf41cec0 · outbound

This paper cites Gated Delta Networks: Improving Mamba2 with Delta Rule.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Gated Delta Networks: Improving Mamba2 with Delta Rule

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:41.725071Z

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Observation 0f5aac4f-16fb-4efc-bf71-ac88f02f2d32 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher Ré.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:41.849040Z

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Observation cfa26fd2-c47e-4ac2-8d7f-4c5ee3922707 · outbound

This paper cites FlashAttention-2: Faster attention with better parallelism and work partitioning.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling FlashAttention-2: Faster attention with better parallelism and work partitioning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:41.985338Z

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Observation b73e50e4-343c-40fa-9ae8-f6c277297434 · outbound

This paper cites Breaking the Low-Rank Dilemma of Linear Attention.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Breaking the Low-Rank Dilemma of Linear Attention

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:53:47.932366Z

Source-reported events for the cited work

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Observation ccaaa6b4-3d27-43f5-a5ba-444c6474c541 · outbound

This paper cites RMT: retentive networks meet vision transformers.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling RMT: retentive networks meet vision transformers

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:49.475521Z

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Observation 768e8990-c5ed-40b7-a028-43e05d932e6c · outbound

This paper cites Rethinking Local Perception in Lightweight Vision Transformer.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Rethinking Local Perception in Lightweight Vision Transformer

Reference 17

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Observation 267252a0-8207-4b6c-802b-42630874524d · outbound

This paper cites Vision Transformer with Sparse Scan Prior.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Vision Transformer with Sparse Scan Prior

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:53:47.733820Z

Source-reported events for the cited work

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Observation ad8c3daa-e6ac-4713-9af2-e4a3d45b8785 · outbound

This paper cites Semantic Equitable Clustering: A Simple and Effective Strategy for Clustering Vision Tokens.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Semantic Equitable Clustering: A Simple and Effective Strategy for Clustering Vision Tokens

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:42.947948Z

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Observation 2bc5817a-9aa0-42bf-913f-734ea3bb6d36 · outbound

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

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.037815Z

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Observation 780be3d8-9f31-4c44-abeb-3f05f938bc03 · outbound

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

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.192221Z

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Observation 23b43d5e-128a-4cf9-b784-405c7b5b86e2 · outbound

This paper cites Parallelizing Linear Transformers with the Delta Rule over Sequence Length.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Parallelizing Linear Transformers with the Delta Rule over Sequence Length

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.404040Z

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Observation 3c4aa0c4-8e53-47f4-8dce-4cae96768e95 · outbound

This paper cites Titans: Learning to Memorize at Test Time.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Titans: Learning to Memorize at Test Time

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.614720Z

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Observation 810837c5-a31d-4cdf-adc1-e8b5c02230c0 · outbound

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

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Retentive Network: A Successor to Transformer for Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.713012Z

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Observation a1402a76-c35d-43c9-8237-1a7f47eec5e3 · outbound

This paper cites Zoology: Measuring and Improving Recall in Efficient Language Models.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Zoology: Measuring and Improving Recall in Efficient Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.795984Z

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Observation 8f85410b-d17b-454a-b531-445da45ac2df · outbound

This paper cites RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:43.866446Z

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Observation 595f2c3b-fd82-4c71-95a0-cf3ef1181ba8 · outbound

This paper cites ATRI: Mitigating Multilingual Audio Text Retrieval Inconsistencies by Reducing Data Distribution Errors.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling ATRI: Mitigating Multilingual Audio Text Retrieval Inconsistencies by Reducing Data Distribution Errors

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:53:47.428071Z

Source-reported events for the cited work

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Observation 344e05e0-6168-4468-aa52-0fdfcf3bd63e · outbound

This paper cites In-Context Language Learning: Architectures and Algorithms.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling In-Context Language Learning: Architectures and Algorithms

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:44.127841Z

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Observation 72ab3a85-3148-46b9-a74e-6d6349c8d158 · outbound

This paper cites Knowledge distillation: A survey.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Knowledge distillation: A survey

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:44.292245Z

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Observation 3b5a70de-3bed-48bd-99c9-f57e5d1d764f · outbound

This paper cites Understanding and Improving Knowledge Distillation.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Understanding and Improving Knowledge Distillation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:44.368455Z

Source-reported events for the cited work

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Observation cb9b0894-42ac-4dd9-9639-356e2dfd57cc · outbound

This paper cites Distillation Scaling Laws.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Distillation Scaling Laws

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:44.547375Z

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Observation e402c84c-8f4d-4674-aca9-f72a7fb83902 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Distilling the Knowledge in a Neural Network

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:44.746856Z

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Observation bb54d88b-40e4-4618-875d-1763898db942 · outbound

This paper cites Parametric instance classification for unsupervised visual feature learning.Advances in neural information processing systems, 33:15614– 15624, 2020.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Parametric instance classification for unsupervised visual feature learning.Advances in neural information processing systems, 33:15614– 15624, 2020

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:49.310838Z

Source-reported events for the cited work

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Observation 7937192a-d18e-4243-b0dd-381810a358f3 · outbound

This paper cites Peco: Perceptual codebook for bert pre-training of vision transformers.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Peco: Perceptual codebook for bert pre-training of vision transformers

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:49.146834Z

Source-reported events for the cited work

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Observation eb5f47ff-3a91-4c95-999b-9a2164657409 · outbound

This paper cites Simmim: A simple framework for masked image modeling.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Simmim: A simple framework for masked image modeling

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.964219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5f78d5b9-de59-47b1-9af3-b2dc4d9184eb · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Convnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:45.401165Z

Source-reported events for the cited work

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Observation ed883b94-2323-436d-81e7-69c820df6b92 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling DINOv2: Learning Robust Visual Features without Supervision

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:45.570926Z

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Observation 261803a9-9552-40fe-99f8-8e15e57543b6 · outbound

This paper cites Image bert pre-training with online tokenizer.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Image bert pre-training with online tokenizer

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:45.732403Z

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Observation 57452b99-88ad-46a2-aa7d-e20db22d9b67 · outbound

This paper cites Knowledge distillation for fast and accurate DNA sequence correction.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Knowledge distillation for fast and accurate DNA sequence correction

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:53:47.196968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0ef557ae-5954-4480-99ac-574cfef6384b · outbound

This paper cites Self-distillation improves self-supervised learning for dna sequence inference.Neural Networks, 183:106978, 2025.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Self-distillation improves self-supervised learning for dna sequence inference.Neural Networks, 183:106978, 2025

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.791273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f7493f0d-93bf-4dfd-8ee3-89c181a789a7 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:46.196287Z

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Observation 02b1147e-73b7-4704-9925-0b4001562a0f · outbound

This paper cites Genomic benchmarks: a collection of datasets for genomic sequence classification.BMC Genomic Data, 24(1):25, 2023.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Genomic benchmarks: a collection of datasets for genomic sequence classification.BMC Genomic Data, 24(1):25, 2023

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.604275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 222af0b6-2d44-4097-962e-3a1dd93b0696 · outbound

This paper cites Effective gene expression prediction from sequence by integrating long-range interactions.Nature methods, 18(10):1196–1203, 2021.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Effective gene expression prediction from sequence by integrating long-range interactions.Nature methods, 18(10):1196–1203, 2021

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:46.458176Z

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Observation ccf8f2b9-72c9-470e-9cf5-50ed8442d190 · outbound

This paper cites Evaluation of grch38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Evaluation of grch38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.467304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9dbd64b3-f20a-4e21-bec4-b46b78135d6c · outbound

This paper cites Towards a better understanding of reverse- complement equivariance for deep learning models in genomics.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Towards a better understanding of reverse- complement equivariance for deep learning models in genomics

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.333082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7cdbb9c-3a8d-4815-9194-c21723b9167b · outbound

This paper cites Visualizing data using t-sne.Journal of machine learning research, 9(11), 2008.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Visualizing data using t-sne.Journal of machine learning research, 9(11), 2008

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:48.141448Z

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