Paper Citation Record · LEDGER

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

As of 17 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 5 inbound Pith citation observations for arXiv:2505.00315.

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

pith.paper-citation-record.v1
2505.00315 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:52:42.980950Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:50:40.854420Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T23:49:10.742674Z

Reference resolution

70 of 70 outbound references displayed

verified exact0
verified fuzzy44
unresolved25
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ffe46a2-863b-4131-ab72-d1e2c3f6aa17 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.224119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 674f59e8-ccd2-4108-97ed-e8f0ec5351d5 · outbound

This paper cites Language models are few-shot learners.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Language models are few-shot learners

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.207678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91dd2db4-7c89-428d-9f6f-e0d65fd878f6 · outbound

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

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing LLaMA: Open and Efficient Foundation Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.654726Z

Source-reported events for the cited work

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Observation f7a101a1-bf2e-47f8-bfcf-e4ea9790c109 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.660221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48ce76c7-5857-46aa-b289-193c85a33b0b · outbound

This paper cites The Llama 3 Herd of Models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing The Llama 3 Herd of Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.665341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c458f3a-e21d-4839-a237-5d2d2b2276cb · outbound

This paper cites Hippo: Recurrent memory with optimal polynomial projections.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Hippo: Recurrent memory with optimal polynomial projections

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.192500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1bb58af2-4c9a-42a6-8bab-d1ab1a90b995 · outbound

This paper cites Efficiently modeling long sequences with structured state spaces.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficiently modeling long sequences with structured state spaces

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.176868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2aac7d60-4c0f-470f-aac9-af63c01643e5 · outbound

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

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.680870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa12ccc4-ccf4-4ceb-8ffa-a31e03fc3f12 · outbound

This paper cites State Space Model for New-Generation Network Alternative to Transformers: A Survey.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing State Space Model for New-Generation Network Alternative to Transformers: A Survey

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.685702Z

Source-reported events for the cited work

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Observation ac61648f-4276-46d8-810f-49f57fe562f6 · outbound

This paper cites Gated delta networks: Improving mamba2 with delta rule.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Gated delta networks: Improving mamba2 with delta rule

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.160948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05ec2dcc-a059-4b42-8a3b-8d6654176d42 · outbound

This paper cites Can mamba learn how to learn? a comparative study on in-context learning tasks.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Can mamba learn how to learn? a comparative study on in-context learning tasks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.146094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c99e954-aa90-4c3d-bf08-e9a814bf49d9 · outbound

This paper cites Efficient Long Sequence Modeling via State Space Augmented Transformer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.700496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67fb8af9-c2f8-4d10-a259-e0b36483457e · outbound

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

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Jamba: A Hybrid Transformer-Mamba Language Model

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.705462Z

Source-reported events for the cited work

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Observation 8f6f22cd-8b27-4e6c-b2cc-ec3d6af6c1ef · outbound

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

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Transformers are RNNs: Fast autoregressive transformers with linear attention

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.130775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ea397617-3235-4149-936b-8cfced97bd80 · outbound

This paper cites Linear transformers are secretly fast weight programmers.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Linear transformers are secretly fast weight programmers

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.114816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5f9e71b4-79a4-4a3e-a4ac-65cc9b65590e · outbound

This paper cites Learning to control fast-weight memories: An alternative to recurrent nets.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Learning to control fast-weight memories: An alternative to recurrent nets

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.099246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1bbffd0b-34fc-4ef1-af68-49f7f5cc809e · outbound

This paper cites The devil in linear transformer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing The devil in linear transformer

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.084166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0d691b61-08d4-466c-80ad-36e77e8075ea · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Generating Long Sequences with Sparse Transformers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.728840Z

Source-reported events for the cited work

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Observation 4cfdd99c-a404-448e-ad95-aab8059a0385 · outbound

This paper cites Big bird: Transformers for longer sequences.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Big bird: Transformers for longer sequences

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.068864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7efdb529-dcee-4dbf-8c6d-f1ffbc3b2665 · outbound

This paper cites Longformer: The Long-Document Transformer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Longformer: The Long-Document Transformer

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.739379Z

Source-reported events for the cited work

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Observation c6d61473-7ce8-4334-a02b-bb4989fdef97 · outbound

This paper cites Zoology: Measuring and improving recall in efficient language models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Zoology: Measuring and improving recall in efficient language models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.053184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation addfc2b1-0a86-40d9-b487-4a59362fab1e · outbound

This paper cites Repeat after me: Transformers are better than state space models at copying.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Repeat after me: Transformers are better than state space models at copying

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.037376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 97d27218-b36a-437c-a8f8-22d69a02fa89 · outbound

This paper cites Synthesizer: Rethinking self-attention for transformer models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Synthesizer: Rethinking self-attention for transformer models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.018801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee94e54a-849a-4911-948e-6b3bddeb566a · outbound

This paper cites Fast transformers with clustered attention.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Fast transformers with clustered attention

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:44.000975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f2c2e1d2-2661-4b26-8489-8bfa366804bb · outbound

This paper cites Efficient content-based sparse attention with routing transformers.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficient content-based sparse attention with routing transformers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.984740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df8e47a9-ec21-48a9-addb-6d04c5449279 · outbound

This paper cites Convergence properties of the k-means algorithms.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Convergence properties of the k-means algorithms

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.968945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8387212e-ab68-433a-b34f-bc2c855ba7bf · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.952806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6c83f20-df69-4dae-a95b-46562b2bc867 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.936979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86b2eedf-af5c-49a7-bc8a-1e6fbca0fb32 · outbound

This paper cites Mixture-of-experts with expert choice routing.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mixture-of-experts with expert choice routing

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.921276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 40ceb9a9-6dec-4361-bd20-11a248e593fa · outbound

This paper cites Mixture of attention heads: Selecting attention heads per token.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mixture of attention heads: Selecting attention heads per token

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.905349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66d13f37-05af-476e-84c3-2fc369ac3bc5 · outbound

This paper cites Switchhead: Accelerating transformers with mixture-of-experts attention.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Switchhead: Accelerating transformers with mixture-of-experts attention

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.889574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 404a9814-60c1-4209-abab-8565ce79ca5b · outbound

This paper cites Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.873901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 068ccfb6-5994-4b9f-acd8-dfd75eb1e226 · outbound

This paper cites Snapkv: Llm knows what you are looking for before generation.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Snapkv: Llm knows what you are looking for before generation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.858773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8e0e9331-2999-4271-9779-af49e3cf5bc0 · outbound

This paper cites PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.805826Z

Source-reported events for the cited work

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Observation f2a9a438-53bb-41fc-b1fb-d0332739004b · outbound

This paper cites Gshard: Scaling giant models with condi- tional computation and automatic sharding.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Gshard: Scaling giant models with condi- tional computation and automatic sharding

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.842793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b34db213-1b34-4e7e-9ebe-7e090f1a3c82 · outbound

This paper cites Fast Transformer Decoding: One Write-Head is All You Need.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Fast Transformer Decoding: One Write-Head is All You Need

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.815663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 540e4f27-5d6a-413d-a5e0-29a29372d88d · outbound

This paper cites Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.820722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0f0f4a1-1786-4b40-b9bc-752f5ffb27c0 · outbound

This paper cites Approximating two-layer feedforward networks for efficient transformers.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Approximating two-layer feedforward networks for efficient transformers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.826772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9f9b3ef3-6f8a-4be0-8881-7b62eb8a16d8 · outbound

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

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.810921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 260485ec-4af5-4deb-bfdf-929c0c6a062f · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing PyTorch: An imperative style, high-performance deep learning library

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.795491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation efdf7b8b-469b-4b49-bbf9-c64c0cf4550c · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.840198Z

Source-reported events for the cited work

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Observation 20dc7b7d-80f4-4ead-b1a5-75700f890705 · outbound

This paper cites Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.779647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 106e6762-b25e-4913-9f2f-ba02c232126c · outbound

This paper cites Neural machine translation of rare words with subword units.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Neural machine translation of rare words with subword units

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.763986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 13a8ad77-0d31-4b57-8bb4-189a7a2b2451 · outbound

This paper cites Japanese and korean voice search.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Japanese and korean voice search

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.748580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7928e4c9-ef5d-4856-8d7c-a4e71a6318b8 · outbound

This paper cites an unresolved cited work.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:52:43.732176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 52f149fc-d2a9-4d29-b030-70009d6acbb7 · outbound

This paper cites Kingma and Jimmy Ba.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Kingma and Jimmy Ba

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.716134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6927aca1-407f-4441-80c7-bf8056d56456 · outbound

This paper cites Efficient long-range transformers: You need to attend more, but not necessarily at every layer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficient long-range transformers: You need to attend more, but not necessarily at every layer

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.701133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7eaf45c5-b634-4aad-96c7-2ade3ee33bd8 · outbound

This paper cites Efficient streaming language models with attention sinks.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficient streaming language models with attention sinks

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.686297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8a18061e-fa5b-4bd0-b2a7-b2857453d871 · outbound

This paper cites Reformer: The efficient transformer.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Reformer: The efficient transformer

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.670935Z

Source-reported events for the cited work

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Observation a68653d7-a2a5-4ebc-9829-364d2e885a1b · outbound

This paper cites From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models

Reference 50

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Observation 8abcdbb1-12fb-489c-b272-c76849a03c66 · outbound

This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.654662Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 926df9c5-1339-4702-85ee-24bd588191ff · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Winogrande: An adversarial winograd schema challenge at scale

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.637170Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8650606-3e83-4abf-9c84-1a20e0a5ab4b · outbound

This paper cites an unresolved cited work.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:52:43.620251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d6316431-8fcc-4494-a085-b5da17a2ab6b · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proc.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Hellaswag: Can a machine really finish your sentence? In Proc

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.605098Z

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Observation fe870209-235a-49c6-a1a7-b8a962d5a49d · outbound

This paper cites PIQA: reasoning about physical commonsense in natural language.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing PIQA: reasoning about physical commonsense in natural language

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.588331Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3237c19b-e70d-4994-af15-989c465d88ac · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.910654Z

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Observation 9c6e41d7-ed50-42bc-9510-20c0b9faba5c · outbound

This paper cites ST-MoE: Designing Stable and Transferable Sparse Expert Models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing ST-MoE: Designing Stable and Transferable Sparse Expert Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.915842Z

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Observation c682383a-237a-4114-80ae-88bc4e88622b · outbound

This paper cites Mixture-of-experts meets instruction tuning: A winning combination for large language models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mixture-of-experts meets instruction tuning: A winning combination for large language models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.571391Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72b5a80f-a5d2-47f2-9670-fa53bd23be89 · outbound

This paper cites Colwell, and Adrian Weller.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Colwell, and Adrian Weller

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.553736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 37c1e652-bb81-454c-8fea-b1eae7554690 · outbound

This paper cites SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.932977Z

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Unavailable: canonical work link unavailable.

Observation af926aaf-0c33-4cb9-a55f-affd6ca805c8 · outbound

This paper cites HashAttention: Semantic Sparsity for Faster Inference.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing HashAttention: Semantic Sparsity for Faster Inference

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.938149Z

Source-reported events for the cited work

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Observation 5470def8-36dd-4460-9cb2-799047e85e25 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.943317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1328b48e-5b56-413a-9dbe-101658e6fea7 · outbound

This paper cites Mixtral of Experts.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mixtral of Experts

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.947854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dd3f17d-e420-4b1e-820c-a11159d64c59 · outbound

This paper cites JetMoE: Reaching Llama2 Performance with 0.1M Dollars.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing JetMoE: Reaching Llama2 Performance with 0.1M Dollars

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.952805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2649bc52-0510-4976-843f-38fce4bc8391 · outbound

This paper cites BASE layers: Simplifying training of large, sparse models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing BASE layers: Simplifying training of large, sparse models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.536768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ddd8c8bf-02a6-4bc5-88ec-d1072d47624e · outbound

This paper cites Hash layers for large sparse models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Hash layers for large sparse models

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.519827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9ffbcb7-b545-4f82-bb0b-6c49303dc3f0 · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.966946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24d6827b-5f61-4018-91df-4fb99563fb41 · outbound

This paper cites Moh: Multi-head attention as mixture-of-head attention.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Moh: Multi-head attention as mixture-of-head attention

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.971702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66ae2599-b207-4fed-a290-21723eca9b69 · outbound

This paper cites Gqa: Training generalized multi-query transformer models from multi-head checkpoints.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Gqa: Training generalized multi-query transformer models from multi-head checkpoints

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:52:43.503341Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a5ae2b1d-17f2-4fc4-b392-5bc6efd3458e · outbound

This paper cites On layer normalization in the transformer architecture.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing On layer normalization in the transformer architecture

Reference 70

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T04:52:43.486226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 0f65d681-9848-4316-9905-dd2d8b9b35f1 · inbound

Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free cites this paper.

Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T09:04:34.904141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f4cc3e69-8378-4209-97ef-a5df07deff95 · inbound

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention cites this paper.

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:50:40.854420Z

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Unavailable: canonical work link unavailable.

Observation 4f23b4b7-3f5f-4dcb-ba2f-797b46b5f675 · inbound

Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.

Kimi Linear: An Expressive, Efficient Attention Architecture Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:49:10.746854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f25861fd-44c6-427a-8979-dc85ce5d1a07 · inbound

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models cites this paper.

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T04:55:42.586782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcfbf863-46b7-49e3-a72a-577cafc0a4c3 · inbound

Compressed Sensing for Capability Localization in Large Language Models cites this paper.

Compressed Sensing for Capability Localization in Large Language Models Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T01:00:44.103650Z

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Unavailable: canonical work link unavailable.