Paper Citation Record · LEDGER

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 5 inbound Pith citation observations for arXiv:2506.09507.

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

pith.paper-citation-record.v1
2506.09507 v3

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:55:36.237994Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:25:17.270632Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T11:53:15.197886Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy15
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0797729a-8eea-41dd-9f2e-547ccf27cf3b · outbound

This paper cites Variational learning for switching state-space models,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Variational learning for switching state-space models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:40.130131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ea0c4b52-48f7-4a0a-94cd-487917cf58e7 · outbound

This paper cites Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:39.866342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e2129d36-77e3-4fd5-b471-9598ee5220d4 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Jamba: A Hybrid Transformer-Mamba Language Model

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.295247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eab9e81-ae7b-4557-afda-57448237805e · outbound

This paper cites Attention is all you need,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Attention is all you need,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.409076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb380167-b69d-4ce1-92b3-040b9ed3ad3c · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding An Empirical Study of Mamba-based Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.498254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f4b7860-0fc9-42cc-897f-bb7568780c11 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.572401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cef0914-765c-4a51-8b09-bccfe07b8884 · outbound

This paper cites Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.641409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e51c30e-d749-425a-8772-8cd8fc2e2064 · outbound

This paper cites Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.712411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d62783e-2c8c-4dd6-ad25-811950766939 · outbound

This paper cites Stuffed mamba: State collapse and state capacity of rnn-based long-context modeling,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Stuffed mamba: State collapse and state capacity of rnn-based long-context modeling,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.771209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1609cb38-dc68-4e7d-be0c-b4819fa450ed · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.834731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation befa38f3-c6d1-4fc0-a38f-910f895dcf82 · outbound

This paper cites Block-state transformers,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Block-state transformers,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:39.690455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9ae792ea-9a61-4696-bce5-787860c22442 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.979564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a7d6c5b-b713-43a8-87e3-a3902a149e54 · outbound

This paper cites Hungry hungry hippos: Towards language modeling with state space models,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Hungry hungry hippos: Towards language modeling with state space models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:39.512165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28fa0496-64dc-4012-8613-ba9d27f12345 · outbound

This paper cites Hyena hierarchy: Towards larger convolutional language models,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Hyena hierarchy: Towards larger convolutional language models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:39.341300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 61e9aa88-d29e-4a7d-bf6d-231e7f896a73 · outbound

This paper cites StripedHyena: Mov- ing Beyond Transformers with Hybrid Signal Processing Models,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding StripedHyena: Mov- ing Beyond Transformers with Hybrid Signal Processing Models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:39.101321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6f79744f-9d66-42f6-a752-f3894887b198 · outbound

This paper cites Mistral 7B.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Mistral 7B

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.190786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 346683a6-6986-4b34-b662-aa82ca73e994 · outbound

This paper cites Multi-head state space model for speech recognition,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Multi-head state space model for speech recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:38.796661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cc46cb1c-ef00-4038-ae64-463dbec15de4 · outbound

This paper cites Diagonal state space augmented Transformers for speech recognition,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Diagonal state space augmented Transformers for speech recognition,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:38.428249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cc0c7b7f-f761-4314-94b6-5dcc6db4d676 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Can mamba learn how to learn? a comparative study on in-context learning tasks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:38.171209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1d25165b-0d43-4fe5-a272-ecda181d0230 · outbound

This paper cites The Llama 3 Herd of Models.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding The Llama 3 Herd of Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.427048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50ff4394-4e08-4d03-a0f7-e76f14402f5d · outbound

This paper cites Smollm-corpus,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Smollm-corpus,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:37.858653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c52901a-a011-49a5-9449-7752545ffcb1 · outbound

This paper cites GPT-NeoX-20B: An Open-Source Autoregressive Language Model.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding GPT-NeoX-20B: An Open-Source Autoregressive Language Model

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.556799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c44654c9-e0f5-4dae-a09e-be099567c5a1 · outbound

This paper cites Transformers: State-of-the-art natural language processing,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Transformers: State-of-the-art natural language processing,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.620506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20f5a6bf-25f5-4200-951a-3060a6717a75 · outbound

This paper cites A framework for few-shot language model evaluation,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding A framework for few-shot language model evaluation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.694298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abd61283-2a1a-4967-81f0-b8a883960bd8 · outbound

This paper cites Measuring massive multitask language understanding,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Measuring massive multitask language understanding,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:37.492260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f8295b12-d722-4b5c-8051-b0d5e5037331 · outbound

This paper cites Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension,.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:37.166119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6bf752df-959a-4398-b6a7-693f5b56e512 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.891647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e84384ff-2eb2-4e03-8d80-e8607a8edf46 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding PIQA: Reasoning about physical commonsense in natural language,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:36.968676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1335da12-48d6-4ca0-b451-a57747595434 · outbound

This paper cites HellaSwag: Can a machine really finish your sentence?.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding HellaSwag: Can a machine really finish your sentence?

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:36.758909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c872ab73-a84b-4230-b98a-a69a40b67bf1 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:36.134083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01fce22d-aea2-41ed-842a-6e87bfca2391 · outbound

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

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Winogrande: An adversarial Winograd schema challenge at scale,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:55:36.652192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 015945b7-9d6f-4f78-a689-ef3f43eeb132 · inbound

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation cites this paper.

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:01:46.169783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b9e366f-bc2b-4ff4-8918-a15398ea724d · inbound

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation cites this paper.

Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-05T10:25:17.270632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c59413-7788-4878-bf2d-7307ab423bb0 · inbound

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling cites this paper.

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:01:10.786478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c6bc0eb-741b-4884-a5f6-101d4910c66f · inbound

The Transformer as a Polar State Estimator cites this paper.

The Transformer as a Polar State Estimator TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Reference 193

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:17:07.486113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 63b838e0-fb39-4f41-a26b-33ff9f05f870 · inbound

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models cites this paper.

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:53:15.199901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.