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Paper Citation Record · LEDGER

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 5 inbound Pith citation observations for arXiv:2507.05714.

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

pith.paper-citation-record.v1
2507.05714 v3

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:24:53.797281Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:47:45.660904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T03:37:35.708363Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b285bd9e-ecb5-4cfd-ae79-8ed53d6b22c3 · outbound

This paper cites an unresolved cited work.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-06T19:24:50.104228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:50.104228Z digest=sha256:69d7f441369bde5d97882e50d02826142515e9a684908e65bd4587c527fa1ab9

Observation a5c7e7ee-67ee-40e0-9bf8-5bd9875c497c · outbound

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

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 2

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no resolver link, observed 2026-08-06T19:24:50.175682Z

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source=arxiv_source observed=2026-08-06T19:24:50.175682Z digest=sha256:0fc38f4faabf46e1b242f43ebd25909e99f75df7a360a5aab6304500a14c5841

Observation b1325591-250e-4530-b20e-607827cc177b · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 3

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no resolver link, observed 2026-08-06T19:24:50.280623Z

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source=arxiv_source observed=2026-08-06T19:24:50.280623Z digest=sha256:979937ce9f1ab6b88196c7af7a219e5f22de78d3d035c63351726614e1bbe830

Observation b07cf664-b701-4a39-a7aa-72b453789ac8 · outbound

This paper cites Benchmarking Large Language Models in Retrieval-Augmented Generation.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 4

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source=arxiv_source observed=2026-08-06T19:24:50.354323Z digest=sha256:0fc8df5067a27e05afd58a68928acc2c8a14631649b6d7b54e2f375c1e822929

Observation d6cebeaa-9a2e-4989-8c0d-e806c60cb19d · outbound

This paper cites Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Reference 5

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source=arxiv_source observed=2026-08-06T19:24:50.451748Z digest=sha256:317b7a739c5fe2e7e4b5053a4dedc518dc80351ab476f3d7174740de63505592

Observation d37c01da-dbcd-4b92-bc8f-ac116584881e · outbound

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

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 6

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:50.534280Z digest=sha256:e7db40c94fd7cba00afcc9437f82576f30ae6f579a40671a62cd3872b020e324

Observation 309fb8df-4ce8-48bf-b4e7-981d0b64a3f5 · outbound

This paper cites Re2G: Retrieve, Rerank, Generate.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Re2G: Retrieve, Rerank, Generate

Reference 7

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source=arxiv_source observed=2026-08-06T19:24:50.608052Z digest=sha256:522d2a7181b590a08fdba675983e4d80286f4c9c3d17407bb5deaec94027df8e

Observation f4a896c2-f4d9-4344-88b9-9813e301bf22 · outbound

This paper cites The Llama 3 Herd of Models.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation The Llama 3 Herd of Models

Reference 8

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source=arxiv_source observed=2026-08-06T19:24:50.687299Z digest=sha256:3d8258a98ba6046c92d4d21f58c718cfb8a3d0d46e18470abf9e8626ad091076

Observation ebfb0b45-304b-4ffd-a170-aba67ea014cc · outbound

This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation REALM: Retrieval-Augmented Language Model Pre-Training

Reference 9

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source=arxiv_source observed=2026-08-06T19:24:50.762672Z digest=sha256:55b5e1eb6acc8162d88f67409963a334750bacfcee2f5cdb22cc7134656b8298

Observation e84d8c5a-315c-4216-9660-6d8ee4430295 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 10

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source=arxiv_source observed=2026-08-06T19:24:50.862128Z digest=sha256:56351e3566cabdbabce7ed8798be20a6670e9893bab9f20e3c03277d8d0ade23

Observation 1b074398-5056-4add-82ed-72cb467ee1e8 · outbound

This paper cites Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

Reference 11

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source=arxiv_source observed=2026-08-06T19:24:50.937376Z digest=sha256:2923a31a660c79ebd9dc03b484b67264210fa8dd3b1223edb0894ae60c1e4be1

Observation 75de11d2-0a5d-49cc-bb96-2c5cfa176d76 · outbound

This paper cites PubMedQA: A Dataset for Biomedical Research Question Answering.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation PubMedQA: A Dataset for Biomedical Research Question Answering

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.044477Z digest=sha256:1dacdf4106649ff7ba92337e8c00d67f04f7168c32e8ad84823115ad9f16c152

Observation 30025f82-6b1a-427e-b7ad-024588f0a936 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.129296Z digest=sha256:c5994f4127a4b433844d6658d06d2ae678811e72194b4887b2d994cc69e97cb8

Observation 220e272e-14df-468a-951d-2c453ad08e2f · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 14

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source=arxiv_source observed=2026-08-06T19:24:51.212243Z digest=sha256:2888c62bec5a1e172c47934b281725c7e88eff5d7b545aa8be42550a2535dfab

Observation 5dfd4035-795f-4bb1-a325-145dd1ea584f · outbound

This paper cites Evaluating Verifiability in Generative Search Engines.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Evaluating Verifiability in Generative Search Engines

Reference 15

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no resolver link, observed 2026-08-06T19:24:51.275802Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.275802Z digest=sha256:460ab46a0cd31fa5de1ae2de620c970a3b2ab59c0531adc0ce0bcd5e5804e609

Observation 0e1fcf93-988f-465b-a8a3-acc6eb8bf42f · outbound

This paper cites ChatQA: Surpassing GPT-4 on Conversational QA and RAG.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation ChatQA: Surpassing GPT-4 on Conversational QA and RAG

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.379621Z digest=sha256:a1858cd2d256a8675ede08c3a3b782fec3628c10db8e1820ff196a9fd48e4081

Observation 71886768-6fbb-4795-894c-9096ba29b245 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 17

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.468480Z digest=sha256:ccac0393060f1d9b05d5cbcf5ff1801a2a733eb2b659678fa13bfb0536a5aa0d

Observation 0ee91bf1-5067-4c31-b46f-9db94a0af3f4 · outbound

This paper cites GPT-4 Technical Report.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation GPT-4 Technical Report

Reference 18

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source=arxiv_source observed=2026-08-06T19:24:51.530008Z digest=sha256:4b7217e31e09a618c2d68315cd15c06c26e255a5665ed0617e4f327f799ff0a6

Observation 4481cc7b-1372-4743-ba5a-8e0fe63fab75 · outbound

This paper cites In-Context Retrieval-Augmented Language Models.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation In-Context Retrieval-Augmented Language Models

Reference 19

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source=arxiv_source observed=2026-08-06T19:24:51.610954Z digest=sha256:e348cfea6b969179afa131806986acd68342fc5db4c550c7721a504ff2aade55

Observation 50a07832-9a34-4150-8f29-d289a2840f83 · outbound

This paper cites Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering

Reference 20

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.809937Z digest=sha256:2cdc3a4f522a2ca5a8b6873c1c3b49c9ef47ab08eea9c57b4490818ead0ab56f

Observation 069f6937-a358-4d54-9bac-7bd76e8d40a7 · outbound

This paper cites Large Language Models Can Be Easily Distracted by Irrelevant Context.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Large Language Models Can Be Easily Distracted by Irrelevant Context

Reference 21

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source=arxiv_source observed=2026-08-06T19:24:51.991510Z digest=sha256:efa48838c326019d49f0b95f238e36c194c1665170c08d62f3c80047a6a5249c

Observation 214e8902-9a7e-4c43-a26c-c344848ba4a4 · outbound

This paper cites an unresolved cited work.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-08-06T19:24:52.129546Z digest=sha256:77df5b15963962f55bb4178d1d38fcd1817ed155c3f53e2407e36662f553157c

Observation b3224de9-dd24-4770-a883-bd42f3eedfef · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 23

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source=arxiv_source observed=2026-08-06T19:24:52.238510Z digest=sha256:b808d5d5d5c2562eb5c15eaf76e0a863b9f9e5584bf6826be1a0854e0000e45f

Observation e0703914-dbb0-46e3-9d1e-d1cd8873fdb2 · outbound

This paper cites MuSiQue: Multihop Questions via Single-hop Question Composition.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation MuSiQue: Multihop Questions via Single-hop Question Composition

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:52.375707Z digest=sha256:4d81bce010399f8e49beb2ae5ada1c87ff5e81131ef809780dee4afaa1120a51

Observation 4a63383f-ac01-4249-9d2f-f90711f38d47 · outbound

This paper cites InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining

Reference 25

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source=arxiv_source observed=2026-08-06T19:24:52.540163Z digest=sha256:c45d1f4630c295c255bcae8e047140e5331ef21e7abc740a24ce5cbdbdb6852c

Observation e892e0d7-a639-43bc-968c-65bff2afdc1d · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 26

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no resolver link, observed 2026-08-06T19:24:52.704493Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:52.704493Z digest=sha256:2da0216719b67e5d9efab72f935b729c5141690765186a3c45973464c3732184

Observation 85ec07dc-4f2b-421f-b90f-b4ccef465ea1 · outbound

This paper cites InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales

Reference 27

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unresolved
no resolver link, observed 2026-08-06T19:24:52.819484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:52.819484Z digest=sha256:ef7544b03a6bced80a1a529d24bcbe237df1f3f851ec604c6e7eb48969b39b76

Observation 8e300ee3-8d5c-43b1-aa30-ee6dd9a01cc2 · outbound

This paper cites ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities

Reference 28

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no resolver link, observed 2026-08-06T19:24:52.935031Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:52.935031Z digest=sha256:fc71b91aecbdcd6a40273bfa3789525cf007e7a4025ede843b0c900711eaac14

Observation 082d7d84-4e74-4104-accf-a745477d0036 · outbound

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

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 29

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unresolved
no resolver link, observed 2026-08-06T19:24:53.055003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.055003Z digest=sha256:28568c28cfc116a9e21346e93a68b5de0a0c828a86a319f2285821984df09a1c

Observation 8186e39a-1615-4be8-8e25-e1a19f271971 · outbound

This paper cites RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs

Reference 30

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unresolved
no resolver link, observed 2026-08-06T19:24:53.214443Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.214443Z digest=sha256:76899cb23969efb71e88e6f7b7efe65eeed7b6e293ac9c7c002a0d4e6e6e226f

Observation 1005dd11-28af-48d4-9469-ea35a027c9ef · outbound

This paper cites RAFT: Adapting Language Model to Domain Specific RAG.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation RAFT: Adapting Language Model to Domain Specific RAG

Reference 31

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unresolved
no resolver link, observed 2026-08-06T19:24:53.356483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.356483Z digest=sha256:247704d0df9fc543c9af04b7fef662d5a9dbe0ec9d82c4efe3acf0512def0ebc

Observation 130ef53c-4e31-4e0d-9f89-e9ece8e44098 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 32

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unresolved
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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.481397Z digest=sha256:9ceb38724987af15c9d4145e0a641f67a0a21ea27731eb4ddad33f2d8ba52fea

Observation 2d76cc8f-01e4-4f5c-b565-8a8e0e7ec754 · outbound

This paper cites An Empirical Study of Retrieval Augmented Generation with Chain-of-Thought.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation An Empirical Study of Retrieval Augmented Generation with Chain-of-Thought

Reference 33

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verified exact
local_arxiv, observed 2026-08-06T19:24:54.036798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:24:53.596252Z digest=sha256:ccc38b6b766c882c2a6632c25b107d02b92e3de63b7ad581d7e4d786b5479efe

Observation 169d601d-b35c-4499-acf3-a29ab54ef980 · outbound

This paper cites online" 'onlinestring :=.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation online" 'onlinestring :=

Reference 34

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.694085Z digest=sha256:af2e6d57e0a59a2b2b7385f766b31dd3d7ce863417bd8325b5497c7ead8557ff

Observation 06d75e68-9222-459a-95b1-411ac94e89fa · outbound

This paper cites write newline.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation write newline

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:53.797281Z digest=sha256:1f4a05e3edb3c874be9a3c50554b7920127b854e19c087305135cb370cadd060

Pith citing papers

Observation 5410abcd-323d-4eda-9299-0e1f976fb587 · inbound

PRGB Benchmark: A Robust Placeholder-Assisted Algorithm for Benchmarking Retrieval-Augmented Generation cites this paper.

PRGB Benchmark: A Robust Placeholder-Assisted Algorithm for Benchmarking Retrieval-Augmented Generation HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:47:45.660904Z digest=sha256:68a9a4d6352e2bdbd43a88b410d2513da7b93c4914a8cd1050bcca4aa54a672e

Observation 03cc28d5-51a9-45a6-a2b9-70c56cd2a168 · inbound

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework cites this paper.

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T13:36:37.428094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:36:37.428094Z digest=sha256:1f39f3cf6d5c0fff07dcdb515f6cd0bcabbbac5c0507d38b5697f03d787643ad

Observation b134669c-86b4-4150-abd2-128c5497525b · inbound

GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs cites this paper.

GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:42:13.034968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T23:41:47.052697Z digest=sha256:2d970fcdfaa8c28d6201e6d7c1bcbfc7b960632c08d0c95841fc8d314d7226c1

Observation 6a3a2c9d-a5ce-4e5c-8e1b-876e0b73d67a · inbound

EviProp: Seeded Relevance Diffusion on Chunk-Page Graphs for Long Multimodal Document Retrieval cites this paper.

EviProp: Seeded Relevance Diffusion on Chunk-Page Graphs for Long Multimodal Document Retrieval HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T03:37:35.709790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T15:04:30.757297Z digest=sha256:eeeed2cfd155b79c4121b743ed53ab8f19dd4dcc9952196e813a3b541932e3da

Observation 8fbe1941-3538-44bb-bd79-53e16ecdb974 · inbound

SemFlowRAG: Directed Semantic Flow from Abstraction to Evidence for Complex Reasoning cites this paper.

SemFlowRAG: Directed Semantic Flow from Abstraction to Evidence for Complex Reasoning HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T15:25:48.121831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T01:31:23.993255Z digest=sha256:167b59bd24fa630cf26f1027b7b22da276314b216eb11f0b9d611b11e3d6b711