Paper Citation Record · LEDGER

Maximally-Informative Retrieval for State Space Model Generation

As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2506.12149.

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

pith.paper-citation-record.v1
2506.12149 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:03:47.725262Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy4
unresolved34
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

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Outbound references

Observation d436d826-185b-4b76-9794-79844b0b6ba5 · outbound

This paper cites please score these documents.

Maximally-Informative Retrieval for State Space Model Generation please score these documents

Reference 1

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T01:03:48.747132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4edf53fd-7aab-4e4a-89c8-f43ad3f1ea7d · outbound

This paper cites an unresolved cited work.

Maximally-Informative Retrieval for State Space Model Generation Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-07T01:03:48.931527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 51c486a4-fe89-4fe7-bd01-8974ad7de86b · outbound

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

Maximally-Informative Retrieval for State Space Model Generation Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.713390Z

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Observation a8f88f03-ca09-41e8-9e7d-6f602ce8d288 · outbound

This paper cites A Survey on In-context Learning.

Maximally-Informative Retrieval for State Space Model Generation A Survey on In-context Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.797957Z

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Observation 452edcf4-1187-45ff-855c-e0df48949e59 · outbound

This paper cites Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.

Maximally-Informative Retrieval for State Space Model Generation Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.904193Z

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Observation 2fc2fef9-3e96-4494-b0b5-e1bbf0c42994 · outbound

This paper cites Precise Zero-Shot Dense Retrieval without Relevance Labels.

Maximally-Informative Retrieval for State Space Model Generation Precise Zero-Shot Dense Retrieval without Relevance Labels

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.999255Z

Source-reported events for the cited work

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Observation a376758d-84f8-497b-97d4-69c0bc2e842c · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Maximally-Informative Retrieval for State Space Model Generation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.056307Z

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Unavailable: canonical work link unavailable.

Observation 8d88fdc2-6d33-43d0-9b35-74f09d5a7f72 · outbound

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

Maximally-Informative Retrieval for State Space Model Generation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.171934Z

Source-reported events for the cited work

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Observation c57f8f76-13b3-4a30-8ae8-34c19beb42a6 · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

Maximally-Informative Retrieval for State Space Model Generation Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.256425Z

Source-reported events for the cited work

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Observation 2a289bc2-1e89-4892-b14e-a911301816b8 · outbound

This paper cites Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG.

Maximally-Informative Retrieval for State Space Model Generation Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.530451Z

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Observation 3d345cbd-a49f-4ee7-9151-35efa35dd27d · outbound

This paper cites Backpropagated gradient representations for anomaly detection.

Maximally-Informative Retrieval for State Space Model Generation Backpropagated gradient representations for anomaly detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:03:49.255207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a60c1c9-16ec-4f2d-b9b3-f8a724d9926b · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Maximally-Informative Retrieval for State Space Model Generation NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.749772Z

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Observation 8fc54169-f612-455b-bbcd-8a7f21a2cac2 · outbound

This paper cites Making Text Embedders Few-Shot Learners.

Maximally-Informative Retrieval for State Space Model Generation Making Text Embedders Few-Shot Learners

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.821331Z

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Observation 44e5e7e5-209f-4799-a32c-15fde8f20cb3 · outbound

This paper cites SGPT: GPT Sentence Embeddings for Semantic Search.

Maximally-Informative Retrieval for State Space Model Generation SGPT: GPT Sentence Embeddings for Semantic Search

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.996887Z

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Observation a188581d-fe40-43f5-907d-1982621dd0c7 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Maximally-Informative Retrieval for State Space Model Generation MTEB: Massive Text Embedding Benchmark

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.092974Z

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Observation 647218f6-422f-44ab-a1ee-f0f9d6a8ecb7 · outbound

This paper cites Generative Representational Instruction Tuning.

Maximally-Informative Retrieval for State Space Model Generation Generative Representational Instruction Tuning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.158731Z

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Observation 29ffc58b-7840-47fe-88eb-34cc7a3acd1e · outbound

This paper cites Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs.

Maximally-Informative Retrieval for State Space Model Generation Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.232644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b9aafad-f054-4ae3-96bd-d83281a2ade0 · outbound

This paper cites Learning To Retrieve Prompts for In-Context Learning.

Maximally-Informative Retrieval for State Space Model Generation Learning To Retrieve Prompts for In-Context Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.372538Z

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Unavailable: canonical work link unavailable.

Observation 65617e23-9756-471f-9212-a1b2904468cb · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

Maximally-Informative Retrieval for State Space Model Generation REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.454153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11726fce-96ee-470e-b29d-4cf9ce4c43f0 · outbound

This paper cites DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models.

Maximally-Informative Retrieval for State Space Model Generation DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.550391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b834920-2978-4e49-95ab-4adc32723030 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Maximally-Informative Retrieval for State Space Model Generation Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.630333Z

Source-reported events for the cited work

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Observation 353b9b99-d5c4-4d5c-a71b-0a13aa93f396 · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

Maximally-Informative Retrieval for State Space Model Generation LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.435338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc3b28d5-6ef8-4682-a9ed-27341af16e6d · outbound

This paper cites Improving Text Embeddings with Large Language Models.

Maximally-Informative Retrieval for State Space Model Generation Improving Text Embeddings with Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.793211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c102901f-5b9f-4dff-b944-e282343dfe4d · outbound

This paper cites RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation.

Maximally-Informative Retrieval for State Space Model Generation RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.875596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67b3deca-150a-4095-a79f-e02b4da90314 · outbound

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

Maximally-Informative Retrieval for State Space Model Generation Gated Linear Attention Transformers with Hardware-Efficient Training

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.940934Z

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Unavailable: canonical work link unavailable.

Observation 1c9b01fd-0bab-41a8-a2f4-a418aca57d95 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Maximally-Informative Retrieval for State Space Model Generation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:47.011975Z

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Unavailable: canonical work link unavailable.

Observation 88ea77f6-d9d0-47d4-994f-eb7501a612dc · outbound

This paper cites Improving Language Models via Plug-and-Play Retrieval Feedback.

Maximally-Informative Retrieval for State Space Model Generation Improving Language Models via Plug-and-Play Retrieval Feedback

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:47.177878Z

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Observation c63a52f5-da8a-487e-a74e-2c40a13bfbdd · outbound

This paper cites B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory.

Maximally-Informative Retrieval for State Space Model Generation B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:03:47.883607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 96c6e191-6f50-4877-9589-cf024216896c · outbound

This paper cites As explored in previous works, the Mamba2 architecture can be interpreted as linear attention with alearnedcausal mask (Yang et al., 2023; Dao & Gu, 2024; Bick et al., 2024).

Maximally-Informative Retrieval for State Space Model Generation As explored in previous works, the Mamba2 architecture can be interpreted as linear attention with alearnedcausal mask (Yang et al., 2023; Dao & Gu, 2024; Bick et al., 2024)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:03:49.097251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0d0d3704-487e-4147-8966-52b9293da29f · outbound

This paper cites the input state (forward+backward pass through the model) across benchmarks for Mamba2 models.

Maximally-Informative Retrieval for State Space Model Generation the input state (forward+backward pass through the model) across benchmarks for Mamba2 models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:03:48.567778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 94c5acf8-63ad-4e13-8180-a66a5a6180d8 · outbound

This paper cites The red dots represent a gradient optimization trajectory over the question loss landscape starting from the mean context state (green).

Maximally-Informative Retrieval for State Space Model Generation The red dots represent a gradient optimization trajectory over the question loss landscape starting from the mean context state (green)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:03:48.348464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f8a4254e-7d9e-4e91-91ee-a6c8b8797dc2 · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

Maximally-Informative Retrieval for State Space Model Generation M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 2005

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.639300Z

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Unavailable: canonical work link unavailable.

Observation 2edd0261-b578-43f6-91d2-c77c2db1d45c · outbound

This paper cites RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation.

Maximally-Informative Retrieval for State Space Model Generation RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation

Reference 2009

Resolution: malformed identifier; no resolver link, observed 2026-08-07T01:03:46.292777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 621ddee3-13b9-4f86-89ca-9359f729ed7a · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Maximally-Informative Retrieval for State Space Model Generation Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:46.701386Z

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Unavailable: canonical work link unavailable.

Observation 1d6da748-4da5-43cf-b9d0-c09d6537bfd5 · outbound

This paper cites SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation.

Maximally-Informative Retrieval for State Space Model Generation SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:47.103532Z

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Observation 33f10e3c-cfd2-4aca-bd1c-c9c71f84e935 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

Maximally-Informative Retrieval for State Space Model Generation Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.174334Z

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Observation 796e0ac9-9489-4632-9175-4cf972c6ccab · outbound

This paper cites Active Retrieval Augmented Generation.

Maximally-Informative Retrieval for State Space Model Generation Active Retrieval Augmented Generation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.419512Z

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Observation 56947658-e0ed-4554-8a66-0e2c4e56c285 · outbound

This paper cites an unresolved cited work.

Maximally-Informative Retrieval for State Space Model Generation Unresolved cited work

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.349781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c1d01d6-68f4-440a-8796-21d6d4fe050a · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

Maximally-Informative Retrieval for State Space Model Generation MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.232524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a370696-080e-42f2-8982-19a292cbcad6 · outbound

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

Maximally-Informative Retrieval for State Space Model Generation Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:44.532806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52b19520-aa0b-48ef-a54b-7bf1f4ceb81b · outbound

This paper cites Gradients as Features for Deep Representation Learning.

Maximally-Informative Retrieval for State Space Model Generation Gradients as Features for Deep Representation Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:45.909803Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.