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Paper Citation Record · LEDGER

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering

As of 10 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2506.00232.

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

pith.paper-citation-record.v1
2506.00232 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:12:54.713185Z

measured 61 of 61 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T10:10:16.661082Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact1
  • verified fuzzy15
  • unresolved42
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2a2bf7f1-6168-418f-9d7f-facdaa496068 · outbound

This paper cites GPT-4 Technical Report.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:50.274162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.274162Z digest=sha256:f74f28149ec7bebee2710d600474ab0ad3a7468b48838c11aa84bdcccbe4501e

Observation dd702a8f-5c22-46f7-8d1e-02968d455bfc · outbound

This paper cites TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization

Reference 2

Resolution
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no resolver link, observed 2026-08-07T12:12:50.290909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.290909Z digest=sha256:ddc41b63d5d1ee06664c3cde9ce36aa6e2c854457d86408737438e5c45060264

Observation b064e2a9-c739-4dfa-be29-493fc44a2157 · outbound

This paper cites Improving language models by retrieving from trillio ns of tokens.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Improving language models by retrieving from trillio ns of tokens

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:00.673102Z

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=2026-08-07T12:12:50.364185Z digest=sha256:6fba1d75d07b5c1d6f308770c4bc7f6d7dbd63ee61a3de00ec1ac5d2312394fc

Observation 7080d842-fdcb-46eb-8cdb-22fef5200e34 · outbound

This paper cites Language mod- els are few-shot learners.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Language mod- els are few-shot learners

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:00.332325Z

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=2026-08-07T12:12:50.468576Z digest=sha256:868d6d73d94f9ad92997071f7aa44dc833745e330d6c1829a880ded6c66da2cd

Observation b046fa8a-8a51-4e6d-8db0-bd6e083d1a6b · outbound

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

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 5

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unresolved
no resolver link, observed 2026-08-07T12:12:50.516414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.516414Z digest=sha256:803667c767fdd5c8cac4e17376ea76f8f59b2baa50dcec0139db18cec0a580d7

Observation 6b94b0bd-c26c-48e6-a1a2-7bed17040264 · outbound

This paper cites The Faiss library.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering The Faiss library

Reference 6

Resolution
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no resolver link, observed 2026-08-07T12:12:50.552759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.552759Z digest=sha256:b260a1d85cfce7b98fa5a1b34e0b32e2f6cbcfc0ae39446c3772320356bebd43

Observation 7baadc78-0fc9-4f33-a3cf-ac18fd19ebf8 · outbound

This paper cites The Llama 3 Herd of Models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering The Llama 3 Herd of Models

Reference 7

Resolution
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no resolver link, observed 2026-08-07T12:12:50.601126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.601126Z digest=sha256:4d40c9b5bcecc8fb71047d637b1be7bee31210211b5f58596ec4d592ce00ce8c

Observation a5d51a28-9a72-4cd4-a445-3a32da3b6fc9 · outbound

This paper cites A Survey on LLM-as-a-Judge.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering A Survey on LLM-as-a-Judge

Reference 8

Resolution
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no resolver link, observed 2026-08-07T12:12:50.636543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.636543Z digest=sha256:d1a940b39fb15d41c06a282b11c06e8701da6038163542ca269f3eaf7f28dbf6

Observation 33eb8edf-0a14-4353-b588-284847dc739a · outbound

This paper cites Retrieval aug- mented language model pre-training.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Retrieval aug- mented language model pre-training

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:50.726961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.726961Z digest=sha256:f4d85f2f1c180d7259bf280a5023bc76c3f3506727e0e5bfb243403d18025e92

Observation 9a6544ff-3691-471b-98e4-9a9173de2af9 · outbound

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

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 10

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no resolver link, observed 2026-08-07T12:12:50.772066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.772066Z digest=sha256:30adbfb2007081e7d8cc8b6f8828b0579bebf53f8e6a060f3fc667b1eeb59257

Observation 9d51d29d-d139-42de-82ea-b3fcccb57239 · outbound

This paper cites Atlas: Few-shot learning with retrieval augmented language models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Atlas: Few-shot learning with retrieval augmented language models

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:00.096256Z

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=2026-08-07T12:12:50.813325Z digest=sha256:457983ef5bb1d5d15ed8c20c3a40365c1ed9f87ef856d3d7459bcb95b9f574bd

Observation bb2c07f9-33ec-4928-be81-d844494868e8 · outbound

This paper cites Survey of hallucination i n natural language generation.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Survey of hallucination i n natural language generation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:59.816341Z

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=2026-08-07T12:12:50.853967Z digest=sha256:678ef54906234efc3bf8af8231713dd7d943bb87f64f7bb26c529a8eececaf50

Observation bad5df60-7863-4571-93b5-3ee844af2121 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:50.922800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.922800Z digest=sha256:f0232dca8b5dd0767f43b13fc7ffc7db622da60e75cc96b552bc15b9ed4bbc0e

Observation a887edc1-7636-4d14-ac8b-9af3802b5512 · outbound

This paper cites FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research

Reference 14

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no resolver link, observed 2026-08-07T12:12:50.978650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:50.978650Z digest=sha256:e71b32e00f6bf7482c52a6d96002d16e2924dc4e9bc5dcf66fdedf4b11be5705

Observation 65e11b93-ab68-4f51-83e3-b7298ca0bfe8 · outbound

This paper cites SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:51.050892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.050892Z digest=sha256:c5f38c8cd01a2258927d62187a0a568f18229d0756b18748d84c86408c89a51d

Observation 8c33b2e6-8718-4926-ae9d-7682e26f27b9 · outbound

This paper cites RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:51.134973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.134973Z digest=sha256:891613c12a55175c7df8b241ca87fe25980a3a9993d034c2ae87f0b34f27b001

Observation e6cedce8-12c3-4067-ad4a-a2c45f831111 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Retrieval- augmented generation for knowledge-intensive nlp tasks

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:59.440519Z

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=2026-08-07T12:12:51.220777Z digest=sha256:85089bbb7048ae6a542029402e478079270de46bfeeb5df8391f4af788ef6cb8

Observation 06f3618b-6a14-48a7-8435-33113f461228 · outbound

This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Search-o1: Agentic Search-Enhanced Large Reasoning Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:51.279476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.279476Z digest=sha256:dc83682eaba521b94e4a54741b0a928a9478f09c41ccbdad465c1ce463ed55b7

Observation f00a0c21-6089-43e1-99b2-19f84d67a7e7 · outbound

This paper cites KILT: a Benchmark for Knowledge Intensive Language Tasks.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering KILT: a Benchmark for Knowledge Intensive Language Tasks

Reference 19

Resolution
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no resolver link, observed 2026-08-07T12:12:51.315087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.315087Z digest=sha256:9382f656cd5d1655a1a37eccfbee0d57e7e46ce0935922cfee296a9105b3e2ba

Observation c8e696e0-9e11-46a4-ba56-205a5bd1f999 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Measuring and Narrowing the Compositionality Gap in Language Models

Reference 20

Resolution
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no resolver link, observed 2026-08-07T12:12:51.360713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.360713Z digest=sha256:f174d02f1bed9a5477c363222af55f547ab09afd73715305c48ab736ed51698c

Observation 0d6bd54e-d4bb-40bb-9c42-bea4a0bbca4c · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 21

Resolution
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no resolver link, observed 2026-08-07T12:12:51.464695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.464695Z digest=sha256:762a9c499cf2f9b29b513084222a2b30dd9b66e9b660488168739345c62e405e

Observation b8371d11-effc-44e1-ac2c-07874bcfcde4 · outbound

This paper cites Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:51.562830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.562830Z digest=sha256:095374a3984bec12b0b96685bced7b0210a43f88797dffe119859f1ceaded098

Observation 82927590-9c6f-4fa8-9170-b3707016782c · outbound

This paper cites ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:51.669991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.669991Z digest=sha256:b39cd373615c5d7cc3012c3764ff55f4859f9b4d2897416a15b6c497bccaf13b

Observation 837b3e97-0dc4-43df-aa1f-e5d343914099 · outbound

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

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering LLaMA: Open and Efficient Foundation Language Models

Reference 24

Resolution
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no resolver link, observed 2026-08-07T12:12:51.805171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.805171Z digest=sha256:4c259adfac662fc8c97b59aa99e9587061a9f92a860e56cdfb298baafd62e8dc

Observation 8299ca5b-2e92-4206-a229-23cbbe017c6d · outbound

This paper cites ♪ musique: Multihop questions via single-hop question composition.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering ♪ musique: Multihop questions via single-hop question composition

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:59.151924Z

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=2026-08-07T12:12:51.915172Z digest=sha256:0e52c6595aa3623edf8ca41fcf3f161847ee1677fd4131308c434c6c016a4560

Observation 64e53bab-6ce5-4f47-b39d-cc26eed7f705 · outbound

This paper cites Plan*RAG: Efficient Test-Time Planning for Retrieval Augmented Generation.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Plan*RAG: Efficient Test-Time Planning for Retrieval Augmented Generation

Reference 26

Resolution
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no resolver link, observed 2026-08-07T12:12:51.978169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:51.978169Z digest=sha256:b1696ae3cc8f2f108bb677ba4c43bea4f3d77bb3fa1c7f5c138e32bfe8311f63

Observation 6b48723a-5145-475f-a7fb-058b98c2dd86 · outbound

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

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 27

Resolution
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no resolver link, observed 2026-08-07T12:12:52.077629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.077629Z digest=sha256:575391879d4d0b51bc0fa156ee89481659883655fa002b26628128de7c431416

Observation b86d79af-ac85-45fa-a03d-b2bcad60e820 · outbound

This paper cites Chain-of-thought prompting elicits reas oning in large language models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Chain-of-thought prompting elicits reas oning in large language models

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:58.924060Z

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=2026-08-07T12:12:52.131383Z digest=sha256:956f4c6952a0fb9737783a89d924598da68c6a691574a92d735340492d70c00d

Observation 6e0b9527-ea17-47a2-a9c2-69d1129080b6 · outbound

This paper cites GenDec: A robust generative Question-decomposition method for Multi-hop reasoning.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering GenDec: A robust generative Question-decomposition method for Multi-hop reasoning

Reference 29

Resolution
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no resolver link, observed 2026-08-07T12:12:52.186107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.186107Z digest=sha256:d876611b7b6ec9546db056fac6c0b60cee928d63e480696446e764f05f60f774

Observation 99d65b93-7d38-4ef4-a630-a83c57b268c7 · outbound

This paper cites Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:52.255422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.255422Z digest=sha256:082094883590951ccf3b3ebe263bdc44549e56e287cf395e82ec49ae19086f99

Observation 4b075729-1c94-49ab-b24d-0b4821f75ead · outbound

This paper cites Qwen2.5 Technical Report.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Qwen2.5 Technical Report

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:52.336979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.336979Z digest=sha256:ae65d26bc5c474594e675866cf685a9083fb64e4f0a5bc95fff37892698608f5

Observation 86944795-4ebc-419b-aa3d-3adffa2a6574 · outbound

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

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 32

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no resolver link, observed 2026-08-07T12:12:52.429845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.429845Z digest=sha256:168dd9157bb514a3f748ffc37df177f281adfa899a853e2c37c5cf45a53a38f0

Observation 540297d9-3e53-4369-acc1-58fdeb1024a4 · outbound

This paper cites Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models

Reference 33

Resolution
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no resolver link, observed 2026-08-07T12:12:52.492006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.492006Z digest=sha256:21fa74a7abcbaf37650975ee54b061c2ca519fd4b5b4bfc24bc8518bde3354ed

Observation ab5cb329-bd06-4f9d-9b8b-97d8b3890953 · outbound

This paper cites Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:12:54.872020Z

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=2026-08-07T12:12:52.533727Z digest=sha256:ed5777e3f51433f0111be58d26fccbd2c37d728ef9f1ae796a2f8bcf5a8492ca

Observation e03ee049-c628-48ee-92c8-0920c821ef84 · outbound

This paper cites ProcessBench: Identifying Process Errors in Mathematical Reasoning.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering ProcessBench: Identifying Process Errors in Mathematical Reasoning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:52.620513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.620513Z digest=sha256:9a0d4290cb8e48300b5e12fa5d3087f133f52c0c4f6c0717366e92baa4d60a3c

Observation 99b97800-acc8-4355-b6ea-7fe595d3035d · outbound

This paper cites EfficientRAG: Efficient Retriever for Multi-Hop Question Answering.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering EfficientRAG: Efficient Retriever for Multi-Hop Question Answering

Reference 36

Resolution
malformed identifier
no resolver link, observed 2026-08-07T12:12:52.693071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:52.693071Z digest=sha256:875c59a227ee815b73e02c046ae6d39eb8a44ed3bcd1007ad0d8f4a0d8683a5f

Observation d6653f07-a679-42bb-9f73-d6aaf58a08c7 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:58.706163Z

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=2026-08-07T12:12:52.795569Z digest=sha256:25d1bcf9e7f7251dc43a964e6ee354ea7a45db785976f445d40889c9abb8635c

Observation 601e2ad0-9169-438a-8903-7a36b93a4198 · outbound

This paper cites T o perform the comparison, the populations of Canada and Australia must first be individually achieved.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering T o perform the comparison, the populations of Canada and Australia must first be individually achieved

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:58.463190Z

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=2026-08-07T12:12:52.909211Z digest=sha256:879c06ec7b4c98a946a6cb63a383d4d140ad930dc2b5b1f949706fda572f5176

Observation e7cee9b4-0cda-47f1-b8ab-31ba6d2263a6 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:58.310005Z

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=2026-08-07T12:12:52.977049Z digest=sha256:8184abd3b2a7f0669d5def0600632283ed4016956371ccb11f71229c39a4a72b

Observation d4b5cff3-584e-488e-b987-82c516722cde · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:58.174962Z

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=2026-08-07T12:12:53.046701Z digest=sha256:f72b24c5cf0e0dac251f0602d96442c416086c736f2cd91f7c1055c7fb786587

Observation 63bb6c61-1669-4727-af15-ad61eb0d6b31 · outbound

This paper cites Australia has a population o f #2.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Australia has a population o f #2

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:58.047760Z

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=2026-08-07T12:12:53.074481Z digest=sha256:c4ddb58429102e731895267b0f5294c32dd12dde6af41678f7177e62f1bdbf5f

Observation 8867a4a7-1559-4da9-9da0-6943201d0f11 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:57.859694Z

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=2026-08-07T12:12:53.156492Z digest=sha256:10e6b2a86245de444615a20b2d65ec1ea199e12d236ab196f05fbb1548b26153

Observation 3c008805-32a5-4058-af13-34b41a202d90 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:57.706224Z

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=2026-08-07T12:12:53.243312Z digest=sha256:124568034f526d4d08c4761d801da9bd4b10a265de895476c95f62736bd680fa

Observation 601697b1-c7a0-46fe-9963-7bb9ae9ebb06 · outbound

This paper cites The length of Tigris is #2.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering The length of Tigris is #2

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:57.546866Z

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=2026-08-07T12:12:53.323644Z digest=sha256:bc758b8b4270b949da242d5ab9f44c1282db5bc70c844a906f8940b0d0b1fc31

Observation acd3f197-31d0-457b-a5bc-123554a956a8 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:57.439451Z

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=2026-08-07T12:12:53.402831Z digest=sha256:6ccee2c0095eda8d7f2e3fdede4afe87283d7145e8a73776e8af1faadc257f3a

Observation aff6d78b-91b0-41cd-89fc-4d0591f6ebbb · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:57.272448Z

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=2026-08-07T12:12:53.433102Z digest=sha256:63a2734e7d8c277538e3c8400d3f54f2b8d2ff9ef8a66c7265ca8d2386006990

Observation de86dbe8-aec7-4258-80ce-c59e47195ac0 · outbound

This paper cites Once both are identified, their geographical di stance can be obtained.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Once both are identified, their geographical di stance can be obtained

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:57.108918Z

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=2026-08-07T12:12:53.482120Z digest=sha256:44475df69b211f2f641508450a6f5472fb855147c5cefa057f188eed18aaf144

Observation 8b3ae6a5-7aac-491e-aa2a-1980b78a8c88 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:56.969155Z

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=2026-08-07T12:12:53.528577Z digest=sha256:515089b075fec4bf4324c7e74d1e6af66f4f37b2c99a9d7827eb09f0312b2808

Observation c7c13d0f-7616-4233-979c-7c402e810b08 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:56.817450Z

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=2026-08-07T12:12:53.656495Z digest=sha256:3877bfa9ac25157c27507a78a09cc87b5e4f1bdd4479c219413e380c5384609c

Observation 4009c79f-132f-4f50-9a99-9e2f5095c91b · outbound

This paper cites First, the country where the Eiffel Tower is loca ted must be found, followed by identifying its capital city.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering First, the country where the Eiffel Tower is loca ted must be found, followed by identifying its capital city

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:56.667904Z

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=2026-08-07T12:12:53.765919Z digest=sha256:bb62f450bc03d5328da0bc50dd44bd8d57f41b629877e9ef685f945040e2194c

Observation 1e74a87e-3c95-457b-978b-0a5e6a540f7b · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:56.482272Z

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=2026-08-07T12:12:53.886175Z digest=sha256:eb8646d24dc3ef17ca934a9687fe58d8ad1a3643970ada7608887a7ade192b35

Observation c9fbae5e-7011-437a-89af-2a2bf03e7b35 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:56.312012Z

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=2026-08-07T12:12:53.943628Z digest=sha256:f5ed09e0477e8640e732e9d77bc092931a5d5e0af5a8877b6c54559ace916d8a

Observation 28848d23-57af-4fe7-bbf7-2d0360a43ece · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:56.125381Z

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=2026-08-07T12:12:54.050780Z digest=sha256:e1488ef9ce8c995e4b9d3cfe215970d05e15689f15198334d724ae55e14864c2

Observation 87f4dc02-575e-44ce-adaa-73577043a910 · outbound

This paper cites #number", don’t use the.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering #number", don’t use the

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:56.014590Z

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=2026-08-07T12:12:54.138453Z digest=sha256:1b4172a95559e36ab05f47b8998c3cb4c41a3e89848d7eabfc046ce2225c0ee6

Observation 8df871b4-c098-4115-ab17-ffd721d2f37d · outbound

This paper cites Instead of asking about where th e company is located, specify that we need the **headquarters** location.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Instead of asking about where th e company is located, specify that we need the **headquarters** location

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:55.557421Z

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=2026-08-07T12:12:54.404979Z digest=sha256:1c2f74ec97779ea34f66f39987f241d331009542615b4406861e2c83949b1523

Observation ebe50fa6-8166-4868-891a-4a60a0c54a91 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:55.846272Z

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=2026-08-07T12:12:54.466524Z digest=sha256:8920eef03095521464b36427b0c7480a51ee333619d73439289510f93edab98a

Observation c3e928c5-0044-41c6-b320-6fd35b25db74 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:55.654939Z

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=2026-08-07T12:12:54.544284Z digest=sha256:485c2de96fd1e5738df2a6794306533a2bea502468a5c501d3442162e8c32ae8

Observation 94169a27-a7d7-4e69-9390-742e0c2dbdc2 · outbound

This paper cites an unresolved cited work.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:12:55.406555Z

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=2026-08-07T12:12:54.613094Z digest=sha256:cb9dcbc242ca6cd5ff0ed1e502876f61bfe48e9b84ac9210ce67db0c039347fd

Observation 69ac44e6-6b8d-4320-9630-8f77828354f8 · outbound

This paper cites Given a question, an answer, and the supporting passages, ev aluate the answer based on the following criteria: a.

ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering Given a question, an answer, and the supporting passages, ev aluate the answer based on the following criteria: a

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:55.217299Z

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=2026-08-07T12:12:54.713185Z digest=sha256:38f7ab4caeabc26752b1ea7b75105e204fc16271473cc5333a80e065ae76c65a

Pith citing papers

Observation f139c760-df11-44b1-8871-f49f6d4df90d · inbound

HyMem: Hybrid Memory Architecture with Dynamic Retrieval Scheduling cites this paper.

HyMem: Hybrid Memory Architecture with Dynamic Retrieval Scheduling ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:00:21.266812Z

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=2026-05-15T21:58:30.784843Z digest=sha256:9d211717f1d24a79ae78edc417fba6e0b6747aeaf5ff5c3e3f6fda1b8cd2a512

Observation 78ef1a62-cf3f-42fc-bd24-7bddc102dfa8 · inbound

Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAG cites this paper.

Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAG ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-06-26T10:29:19.107085Z

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=2026-06-26T10:10:16.661082Z digest=sha256:372ea271c7b27f8432064c8dfeddff3e468ece8d97724cce83ffd1d189c0d1e7