Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:45:35.882329Z
Paper Citation Record · LEDGER
Synergy: End-to-end Concept Model
As of 10 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.12769.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
30 of 30 outbound references displayed
- verified exact1
- verified fuzzy0
- unresolved29
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a73a9e69-35f8-416f-9a22-7ba170a977c3 · outbound
This paper cites online" 'onlinestring :=.
Synergy: End-to-end Concept Model online" 'onlinestring :=
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.489328Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5206c9d5-0e8c-47e5-b2e0-eacf6ce4e34e · outbound
This paper cites write newline.
Synergy: End-to-end Concept Model write newline
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.556667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6e835f4-a804-4501-a480-56ff5a8da5ef · outbound
This paper cites MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization.
Synergy: End-to-end Concept Model MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.629105Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 35c35756-d215-45bd-b73b-f19db2098081 · outbound
This paper cites Longformer: The Long-Document Transformer.
Synergy: End-to-end Concept Model Longformer: The Long-Document Transformer
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.727213Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97250218-9342-4794-8978-a6acb24e5878 · outbound
This paper cites Generating Long Sequences with Sparse Transformers.
Synergy: End-to-end Concept Model Generating Long Sequences with Sparse Transformers
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.788248Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c0644904-4aa5-4f9e-a965-946ec8b6fe35 · outbound
This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.
Synergy: End-to-end Concept Model Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.831893Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5cbcd9f0-034d-421e-a1bb-999aad76db70 · outbound
This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.
Synergy: End-to-end Concept Model Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:33.876998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0143da35-488f-444b-a887-2f0abce2e3fe · outbound
This paper cites Block Transformer: Global-to-Local Language Modeling for Fast Inference.
Synergy: End-to-end Concept Model Block Transformer: Global-to-Local Language Modeling for Fast Inference
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T16:45:36.275908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation df5ba07c-3d6d-494f-b1f5-228867137817 · outbound
This paper cites MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention.
Synergy: End-to-end Concept Model MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.035954Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad746d5b-2b45-4b54-82da-e7c4ccfb0193 · outbound
This paper cites MrT5: Dynamic Token Merging for Efficient Byte-level Language Models.
Synergy: End-to-end Concept Model MrT5: Dynamic Token Merging for Efficient Byte-level Language Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.114874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4f0c9b0-8d44-4c97-b85a-a1d2b5c86ee2 · outbound
This paper cites Large Concept Models: Language Modeling in a Sentence Representation Space.
Synergy: End-to-end Concept Model Large Concept Models: Language Modeling in a Sentence Representation Space
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.210199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16152354-bab5-44ab-a8c0-94113539cf18 · outbound
This paper cites RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval.
Synergy: End-to-end Concept Model RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.301255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 163cec58-7fcd-41df-a1d6-3939de400f21 · outbound
This paper cites MoBA: Mixture of Block Attention for Long-Context LLMs.
Synergy: End-to-end Concept Model MoBA: Mixture of Block Attention for Long-Context LLMs
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.398285Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0c1f0560-80cf-47e6-92f2-3ac25ef99105 · outbound
This paper cites an unresolved cited work.
Synergy: End-to-end Concept Model Unresolved cited work
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.486771Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c4fde03-02e7-4b3e-a922-e05952aca607 · outbound
This paper cites Hierarchical Transformers Are More Efficient Language Models.
Synergy: End-to-end Concept Model Hierarchical Transformers Are More Efficient Language Models
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.588473Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b6c96cd5-26b4-46c5-a8f7-55e1c4d53548 · outbound
This paper cites Byte Latent Transformer: Patches Scale Better Than Tokens.
Synergy: End-to-end Concept Model Byte Latent Transformer: Patches Scale Better Than Tokens
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.701858Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cbcf2ab9-5564-4d60-829d-bfeb09ff547c · outbound
This paper cites RWKV: Reinventing RNNs for the Transformer Era.
Synergy: End-to-end Concept Model RWKV: Reinventing RNNs for the Transformer Era
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.787104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b71ccfb-03c1-40b1-bef8-158f7bde71be · outbound
This paper cites Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence.
Synergy: End-to-end Concept Model Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.859687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4da19791-b547-4688-9bbd-a6e0e19f4904 · outbound
This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.
Synergy: End-to-end Concept Model Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:34.960190Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5034254f-a52f-436d-916e-fd432a6c206f · outbound
This paper cites GLU Variants Improve Transformer.
Synergy: End-to-end Concept Model GLU Variants Improve Transformer
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.018992Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c5bb5ab-f07b-40b5-9d89-2260855c0fd1 · outbound
This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.
Synergy: End-to-end Concept Model RoFormer: Enhanced Transformer with Rotary Position Embedding
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.078091Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cbc1faf9-7c8a-4309-b5cf-d71ec22da923 · outbound
This paper cites Retentive Network: A Successor to Transformer for Large Language Models.
Synergy: End-to-end Concept Model Retentive Network: A Successor to Transformer for Large Language Models
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.130477Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62eb9815-aeae-49c6-bd35-ee650d64bc52 · outbound
This paper cites Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference.
Synergy: End-to-end Concept Model Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.200985Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97e3d855-f6fa-4e91-ba13-2dec5e67755c · outbound
This paper cites MambaByte: Token-free Selective State Space Model.
Synergy: End-to-end Concept Model MambaByte: Token-free Selective State Space Model
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.271646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c57c5eb-7673-432a-a778-07eed5403a9d · outbound
This paper cites Linformer: Self-Attention with Linear Complexity.
Synergy: End-to-end Concept Model Linformer: Self-Attention with Linear Complexity
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.352418Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ce9473c-8423-45c1-824a-e59bf58d3e87 · outbound
This paper cites Efficient Streaming Language Models with Attention Sinks.
Synergy: End-to-end Concept Model Efficient Streaming Language Models with Attention Sinks
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.424748Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30a2b1c2-70bb-4c5f-8a10-9ffeecd0a5f2 · outbound
This paper cites an unresolved cited work.
Synergy: End-to-end Concept Model Unresolved cited work
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.486367Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe5946b5-a58e-4d93-8cc2-6d28d41dd271 · outbound
This paper cites MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers.
Synergy: End-to-end Concept Model MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.749317Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 89388682-9a1c-4fb2-916d-88bce4a0cd79 · outbound
This paper cites Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention.
Synergy: End-to-end Concept Model Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.805318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 600423c6-81aa-479f-be0b-42a0a09390ad · outbound
This paper cites H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
Synergy: End-to-end Concept Model H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:45:35.882329Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.