Paper Citation Record · LEDGER

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.02702.

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

pith.paper-citation-record.v1
2501.02702 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:12:13.994672Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

37 of 37 outbound references displayed

verified exact2
verified fuzzy16
unresolved19
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40de1a97-9478-4ca1-bd0b-7c2152b4f1b1 · outbound

This paper cites Language models are few-shot learners,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Language models are few-shot learners,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.914756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ea179cc0-a21e-42e5-80bc-19a072a684a0 · outbound

This paper cites Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.593326Z

Source-reported events for the cited work

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Observation 55f44b0d-5ea8-4251-920f-80f167527976 · outbound

This paper cites Large language models struggle to learn long-tail knowledge,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Large language models struggle to learn long-tail knowledge,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.624957Z

Source-reported events for the cited work

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Observation 91f74f20-c3db-4ed0-af2e-884600cf5582 · outbound

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

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.637097Z

Source-reported events for the cited work

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Observation 5be694d8-bb03-4d01-838d-1919809395f2 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Overcoming catastrophic forgetting in neural networks,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.690442Z

Source-reported events for the cited work

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Observation 1e35345d-eef8-4075-93ad-3a043725e710 · outbound

This paper cites An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.724761Z

Source-reported events for the cited work

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Observation 232d969b-d558-4d2d-b95d-331a9bab514f · outbound

This paper cites Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.736982Z

Source-reported events for the cited work

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Observation 773b4676-48f2-48a5-9de3-1c6516992c16 · outbound

This paper cites Enhancing international graduate student experience through ai- driven support systems: A llm and rag-based approach,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Enhancing international graduate student experience through ai- driven support systems: A llm and rag-based approach,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.700652Z

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Observation 1ebd9d97-d937-4a4f-b5ea-cb0acd652bb0 · outbound

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

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Retrieval-augmented generation for knowledge-intensive nlp tasks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.644875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d4b8bc2-ba3b-46c5-bce1-2b5d03164c2d · outbound

This paper cites Text and Code Embeddings by Contrastive Pre-Training.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Text and Code Embeddings by Contrastive Pre-Training

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.845942Z

Source-reported events for the cited work

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Observation edb5bc4d-a3c6-4a88-ac1b-bfb59bbf98e2 · outbound

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

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.884317Z

Source-reported events for the cited work

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Observation 207444f9-3644-40dd-b5aa-ce3d5bf5af2b · outbound

This paper cites On the dangers of stochas- tic parrots: Can language models be too big?.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance On the dangers of stochas- tic parrots: Can language models be too big?

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.534754Z

Source-reported events for the cited work

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Observation 4ac45ad7-2566-4022-8046-f79ca40d75b1 · outbound

This paper cites Language models are unsupervised multitask learners,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Language models are unsupervised multitask learners,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:12.934754Z

Source-reported events for the cited work

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Observation 2419d16e-101e-4349-8dfe-1c6703231a84 · outbound

This paper cites Palm: Scaling language modeling with pathways,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Palm: Scaling language modeling with pathways,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.324756Z

Source-reported events for the cited work

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Observation 5d5a37c2-edfd-4127-8fb8-c0382587e23d · outbound

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

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 15

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Source-reported events for the cited work

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Observation 32829c30-82c8-4d71-82fb-705fb4db49a9 · outbound

This paper cites Attention is all you need,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Attention is all you need,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.225901Z

Source-reported events for the cited work

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Observation 8dd64cd5-fa31-45dc-b49e-e11f64de0fee · outbound

This paper cites A survey on large language models: Applications, challenges, limitations, and practical usage,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance A survey on large language models: Applications, challenges, limitations, and practical usage,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:17.104820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 598c274e-2c6d-4217-b894-452af4211246 · outbound

This paper cites Retrieving Supporting Evidence for LLMs Generated Answers.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Retrieving Supporting Evidence for LLMs Generated Answers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:13.105521Z

Source-reported events for the cited work

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Observation 2d762338-0e8d-44d7-9301-395e5c493389 · outbound

This paper cites A Bibliometric Review of Large Language Models Research from 2017 to 2023.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance A Bibliometric Review of Large Language Models Research from 2017 to 2023

Reference 19

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Observation cc44fefb-8956-44e6-aef0-9414c838a786 · outbound

This paper cites A non-factoid question- answering taxonomy,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance A non-factoid question- answering taxonomy,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.994841Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d36276a5-386f-4bb3-8daa-d78082cdf648 · outbound

This paper cites Qa dataset explosion: A taxonomy of nlp resources for question answering and reading comprehension,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Qa dataset explosion: A taxonomy of nlp resources for question answering and reading comprehension,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.884750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3adcd002-d2d5-4c70-ad75-e6152f5d9d15 · outbound

This paper cites Multi-domain multilingual question answering,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Multi-domain multilingual question answering,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.759082Z

Source-reported events for the cited work

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Observation f43d0656-6bf9-4a47-8e67-46677c92a7dc · outbound

This paper cites Survey of hallucination in natural language generation,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Survey of hallucination in natural language generation,

Reference 23

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Observation ab2376e2-f47b-4ed1-802f-4dc1686a191e · outbound

This paper cites Augmented Language Models: a Survey.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Augmented Language Models: a Survey

Reference 24

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Observation 13201218-1d89-40aa-970c-b98fb0787bca · outbound

This paper cites Internet-augmented language models through few-shot prompting for open-domain question answering.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Internet-augmented language models through few-shot prompting for open-domain question answering

Reference 25

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Observation ffdc8949-a4ea-4758-80f9-b534e95fa1c2 · outbound

This paper cites Paq: 65 million probably-asked questions and what you can do with them,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Paq: 65 million probably-asked questions and what you can do with them,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.334835Z

Source-reported events for the cited work

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Observation 193d2dc4-6766-43f9-bbda-de99b11eb97a · outbound

This paper cites A Reliable Knowledge Processing Framework for Combustion Science using Foundation Models.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance A Reliable Knowledge Processing Framework for Combustion Science using Foundation Models

Reference 27

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Source-reported events for the cited work

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Observation 454c0ed9-4d14-4b7b-8169-15e22825f6c7 · outbound

This paper cites Conditioning chat-gpt for information retrieval: The unipa- gpt case study,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Conditioning chat-gpt for information retrieval: The unipa- gpt case study,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.244795Z

Source-reported events for the cited work

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Observation 862cf42d-ec97-4045-884f-ff265d0dbbc3 · outbound

This paper cites Reinforcement Learning for Optimizing RAG for Domain Chatbots.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Reinforcement Learning for Optimizing RAG for Domain Chatbots

Reference 29

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Observation 90eebace-5789-4c2a-b268-6af24b566d6b · outbound

This paper cites QUADRo: Dataset and Models for QUestion-Answer Database Retrieval.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance QUADRo: Dataset and Models for QUestion-Answer Database Retrieval

Reference 30

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Observation 30729bb4-08c2-4ee4-83c2-e1378e4a0f9b · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance MTEB: Massive Text Embedding Benchmark

Reference 31

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Source-reported events for the cited work

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Observation 501623f5-6719-4595-be19-cb09ad0e374d · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance BERTScore: Evaluating Text Generation with BERT

Reference 32

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This paper cites Ragas: Automated Evaluation of Retrieval Augmented Generation.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Ragas: Automated Evaluation of Retrieval Augmented Generation

Reference 33

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This paper cites Rouge-ss: A new rouge variant for the evaluation of text summarization,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Rouge-ss: A new rouge variant for the evaluation of text summarization,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.141621Z

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Observation b5d381c0-066d-4a3a-9aed-800fadc66242 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments,.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Meteor: An automatic metric for mt evaluation with improved correlation with human judgments,

Reference 35

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Observation fc17913e-23c7-4de3-9c0d-7db92aded96c · outbound

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QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Rouge metric evaluation for text summarization techniques,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:15.983975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2d4556a6-acf3-41d4-ae04-93776a940e34 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID:245289877.

QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance Available: https://api.semanticscholar.org/CorpusID:245289877

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:12:16.616296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.