Pith. sign in

Paper Citation Record · LEDGER

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks

As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 3 inbound Pith citation observations for arXiv:2505.14212.

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

pith.paper-citation-record.v1
2505.14212 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:41.769511Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T11:07:25.667648Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:45:42.818877Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact3
  • verified fuzzy17
  • unresolved27
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 883f2447-cdd6-4e91-a1ce-e4c60fea91d8 · outbound

This paper cites A bert baseline for the natural questions.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks A bert baseline for the natural questions

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:45.992196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:36.973217Z digest=sha256:120d7a5c2c4fa907b345a88ffd4ab0ae884d8adb8203adfe2acaa893bca6b5cd

Observation 83f50275-8c56-4628-8269-31f3c292f8ea · outbound

This paper cites Self-RAG: Learning to retrieve, generate, and critique through self-reflection.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Self-RAG: Learning to retrieve, generate, and critique through self-reflection

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:45.757436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:37.098029Z digest=sha256:ea8efd4dd5dda3d1b93f4535236ae8e4ec520d0c55474a120874afe25fbbed99

Observation ca39461f-c058-42d9-89d4-e561298ec2c3 · outbound

This paper cites RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.200193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.200193Z digest=sha256:cbbbcb1b54680ecf5ebd6d8729388815b3d0af2a0defc8f1ade06fe3537dc7a7

Observation dd170161-37f0-4969-b722-c72937590584 · outbound

This paper cites Seven Failure Points When Engineering a Retrieval Augmented Generation System.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Seven Failure Points When Engineering a Retrieval Augmented Generation System

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.271291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.271291Z digest=sha256:b7af66e15ca8202b518af3e5388fb7e94fa7f612aef42d1dba8c1cb54f048478

Observation 3ea29277-ef8a-4336-a335-707891d956e3 · outbound

This paper cites Language models are few-shot learners.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Language models are few-shot learners

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.366055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.366055Z digest=sha256:d6faf1803fadf15807084a0aaf7908c8c9efc49dbb9ffccb944adb594aa764e8

Observation 0d601c7b-8cbc-4cb2-abda-a3c6b8e0aea8 · outbound

This paper cites Language Models are Few-Shot Learners.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Language Models are Few-Shot Learners

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.430426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.430426Z digest=sha256:fc19c960bc5da359b6f43e6a5c8e57f68b6d05fbcd442fcedb4d3bd45735a0a8

Observation c64f706d-1e08-4ef6-b426-535fd1b856ce · outbound

This paper cites The TechQA dataset.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks The TechQA dataset

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.540607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.540607Z digest=sha256:de2d9d64853747bdfbd28f4e7ed9e9c7fb5277b6bdfe6b68dcfc832f8c2cdca2

Observation e4fd9083-19f5-48eb-bf40-16f9b1087172 · outbound

This paper cites Legal-bert: The muppets straight out of law school.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Legal-bert: The muppets straight out of law school

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:45.541323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:37.676038Z digest=sha256:e70b99df946bd3462fa8d43a0d3d22beaf9ccbab6740d8e73680387918ebd532

Observation 0021b0f8-e8f2-41f5-9f00-adbd17bedbb1 · outbound

This paper cites Reading Wikipedia to answer open-domain questions.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Reading Wikipedia to answer open-domain questions

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:37.774638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:37.774638Z digest=sha256:853b09f92b04d5c92a51960f8ae55dcf33fdbcfdf11716193f29972b0b44ebfd

Observation 872002b5-8c2f-4c60-b592-04e8b037ce88 · outbound

This paper cites Dialog inpainting: Turning documents to dialogs.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Dialog inpainting: Turning documents to dialogs

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:45.334160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:37.895457Z digest=sha256:0bdb08deae7ceaf9ec3f4588fcc19cdd182d2971be0a6895f2a19c250f7efb6d

Observation 5c4d2bce-3afd-4cb0-a92c-f7b844f20dea · outbound

This paper cites Unsloth, 2023.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Unsloth, 2023

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:45.163237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:37.956956Z digest=sha256:25d60ddca99772899bec194f126fd83e728cba18522aa3ea3e779522de137eed

Observation ea3b9f92-27c1-4202-a383-9ab2cab21d32 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks QLoRA: Efficient Finetuning of Quantized LLMs

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.104744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.104744Z digest=sha256:87b4e8a9cfaacbbe41fa8e5dd75a30188eebbfb5f59ce8c078fe8a675768ddfb

Observation aadc6bb6-0e39-492a-b903-a1162bd243f6 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.208343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.208343Z digest=sha256:b4c4d88842f6293d5c6df03db2915d7f56a54d4ec6201b6261b83e18b5825def

Observation 31a48569-3b1d-4a5c-9b96-e00af5550e78 · outbound

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

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Precise Zero-Shot Dense Retrieval without Relevance Labels

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.323013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.323013Z digest=sha256:44ae60bfb19f834ffb5a3e9ef5771f660ff106b23e8f75b6817378daee22aa63

Observation 7901d312-a284-4e0f-99cd-3e60c283a006 · outbound

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

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.423678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.423678Z digest=sha256:94f9dc7b1b0a07279237616bdefc87a92281efb8a4a9767b1233aac876ec8d94

Observation f2e4f2ac-d485-4bc0-ad45-8220d626ddb2 · outbound

This paper cites Re2g: Retrieve, rerank, generate.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Re2g: Retrieve, rerank, generate

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.994942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:38.494922Z digest=sha256:f15c8e8cc64c01662372dadf6383d9ef6f54faa284ac7e3e07b186a8171faaf3

Observation e5f892c8-b6b6-4993-b427-575ef4b3688a · outbound

This paper cites The Llama 3 Herd of Models.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks The Llama 3 Herd of Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.597842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.597842Z digest=sha256:c40bae27b3ced52f8c3d72124e2b734ee83fdaea4881638f60068af8f1424eb2

Observation 87de8dff-a5e6-4bb2-b29d-08b3ef5f86d0 · outbound

This paper cites Evaluating large language models in generating synthetic hci research data: a case study.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Evaluating large language models in generating synthetic hci research data: a case study

Reference 18

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-07T15:42:42.436498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:38.709033Z digest=sha256:44558a81b9b1528f33065a8dc576270c9da22e83f8b7b2e7863944c0cb982d24

Observation 3ffc02e1-5c2a-4978-b6de-8bbc44805849 · outbound

This paper cites Retrieve, annotate, evaluate, repeat: Leveraging multimodal llms for large-scale product retrieval evaluation,.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Retrieve, annotate, evaluate, repeat: Leveraging multimodal llms for large-scale product retrieval evaluation,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.807141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:38.798538Z digest=sha256:c0d9c83920028e708828bfebc5033fb345a837c476c77a01b108cc1f4e07ee66

Observation f08ec513-4fb1-4d70-9d52-be6861f8e631 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:38.951239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:38.951239Z digest=sha256:84b0ebe8be9388f3b4fba318cc939d1a388cd29a9ad307bfa489b65a871f47c4

Observation 72f2d793-f29d-4dc3-a963-78f46bbbb289 · outbound

This paper cites Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.041590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.041590Z digest=sha256:4f112ebb1a983e0cdf5563e05ef73d069b2f6ab3660fabce735d076db65b1d91

Observation 1eb595b0-13ea-4f15-8124-23b8988bc241 · outbound

This paper cites Perplexity—a measure of the difficulty of speech recognition tasks.The Journal of the Acoustical Society of America, 62(S1):S63–S63, 1977.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Perplexity—a measure of the difficulty of speech recognition tasks.The Journal of the Acoustical Society of America, 62(S1):S63–S63, 1977

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.151195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.151195Z digest=sha256:73ac87e7763f7e4b74530a3d0bbd3453d13fb5c4d3323ef80cb914753eb44d86

Observation 102530bd-8e0f-4fa2-8d44-c991067c27b6 · outbound

This paper cites Adaptive-rag: Learning to adapt retrieval-augmented large language models through question complexity.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Adaptive-rag: Learning to adapt retrieval-augmented large language models through question complexity

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.658777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:39.239093Z digest=sha256:746a975a3a05ce4b875dec4ae7924e0dfc017d5d6b3905a10f0592dddf3eb1bf

Observation f073ddd3-6836-4d19-a9f6-cc42f293d988 · outbound

This paper cites Mistral 7B.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Mistral 7B

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.438054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.438054Z digest=sha256:88d07128707acaccc7fb89552115a6163611995e71fdb624a786b439d7d8c2a7

Observation 439054b6-2f3f-4481-b59a-806469cfd443 · outbound

This paper cites Weld, and Luke Zettlemoyer.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Weld, and Luke Zettlemoyer

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.512000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.512000Z digest=sha256:0986d0ea29b02843faca95d8a578af229971bcf1f3e27a0440d1b5f6fffc3e8e

Observation 878fe62c-97d1-490b-aa8b-f603eff3e4b0 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Dense Passage Retrieval for Open-Domain Question Answering

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.611689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.611689Z digest=sha256:3338d1f5a6eef620c8a41f4cc5a1cad4e304197a36331092a85b41e50f462286

Observation 7a44a33d-1abb-4ec6-90a9-0d378d35fc2c · outbound

This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.517065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:39.706834Z digest=sha256:519287388a09251323d16817f92df2b8b06964ad4ec327ae74fa07e6d6a54b76

Observation 2aa0f8d1-c564-4a56-bf0a-bd007209b014 · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.822638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.822638Z digest=sha256:2cb5e392eaeebe357d3dccd726f2c56509bcde2dc968b86b07af45fb430a7731

Observation 47d9b97e-b580-45e9-82bd-be61bc545d83 · outbound

This paper cites Synthetic data generation with large language models for text classification: Potential and limitations, 2023.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Synthetic data generation with large language models for text classification: Potential and limitations, 2023

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.361996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:39.919423Z digest=sha256:1e4d3b17bc01f0d5a9dc5024669881b8a6df2bb319429cc17e1f0d19660a9ad9

Observation 14e58741-4e7b-4c09-8ca1-66ffb88798e3 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Rouge: A package for automatic evaluation of summaries

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.989028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:39.989028Z digest=sha256:eb91414ac57f3cf73a5ec58428ebbb72c93675d62560e039548b940fae28bc1b

Observation ad93998d-cbe7-4d35-b0c7-6708318199d0 · outbound

This paper cites RA-DIT: Retrieval- augmented dual instruction tuning.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks RA-DIT: Retrieval- augmented dual instruction tuning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:44.187043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:40.062575Z digest=sha256:6e3d898b114a5394e6813460a11dd0212b5c79a4cbbacdfc15b531fa99135cc3

Observation 8706be44-2056-423f-a05a-14dc3a253a0b · outbound

This paper cites Query Rewriting for Retrieval-Augmented Large Language Models.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Query Rewriting for Retrieval-Augmented Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:40.223793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:40.223793Z digest=sha256:aa863954765dbc4219aa0969e64f504ef1df5564417ab913cfb01f2a15ddf5b1

Observation 109f26a5-9217-4b9b-ab1c-4de610b46857 · outbound

This paper cites an unresolved cited work.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:42:44.018366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:40.159221Z digest=sha256:0124bad32763ad933ccb9513099638a5b765cd923583a1d93c8a41ad9cf0f53a

Observation 7396d248-b413-4692-902e-4641d776686c · outbound

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

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:40.407545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:40.407545Z digest=sha256:f829a09f121784803d743fa598ab543051c0a32b55803cfb2a1734aaf194dab1

Observation 8baded44-eb95-426e-adb2-b9f063e32362 · outbound

This paper cites Synthetic data generation using large language models: Advances in text and code, 2025.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Synthetic data generation using large language models: Advances in text and code, 2025

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:40.310149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:40.310149Z digest=sha256:e3548e4d71c2ca1f6f3dd837df220de3b64c4d11bdc3019f4d0dfea60f7196b6

Observation b79e5b7d-7dad-4dea-9f85-e6cbd58a05e3 · outbound

This paper cites Replug: Retrieval-augmented black-box language models.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Replug: Retrieval-augmented black-box language models

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:43.728246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:40.597237Z digest=sha256:5acc08537560fbe17e4396e5d373694020d41316a9a9655b75713a9b5e6c5b03

Observation ca6187f5-5525-4c81-8e78-61a9c5c3c2b2 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Bleu: a method for automatic evaluation of machine translation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:43.871340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:40.477085Z digest=sha256:219473579cee9b16c0fb88357b0da11a9dddb284d03305f15407af7d5a491349

Observation 1940c952-2775-44e0-af51-091bd059c073 · outbound

This paper cites MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:40.814274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:40.814274Z digest=sha256:48bc13e0b5a8dfe23b62eba7a98d1c62679e3e31006851ae98211e11e83e6db2

Observation a32d2a33-f545-466c-9c95-e9cd0a15d681 · outbound

This paper cites Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:42:41.944474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:40.723536Z digest=sha256:168a827fbfb480cf4196397bf2a63f90eaddef92e92022d3dccbd69b3ec54676

Observation bb6cfa74-840c-4a20-ab11-31254aa7f71a · outbound

This paper cites Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:41.009889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:41.009889Z digest=sha256:196f156f5cb1045a00222d016cd2ae8b83f90839d0957c356208c2234c15bed4

Observation 3362cb33-a730-403e-9b8b-e2e28732e26c · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:40.916194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:40.916194Z digest=sha256:2ce6be2f44c33a9916b839ad6e349ee4978117df587e09d9708be041f482799b

Observation 60f8bb13-fe9a-49ad-a2b8-92a0b2112bf6 · outbound

This paper cites Cohen, Ruslan Salakhutdinov, and Christopher D.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Cohen, Ruslan Salakhutdinov, and Christopher D

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:43.340041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:41.324026Z digest=sha256:0cd52ffeb8f1131360745e268795ea1f3326dbbf1fbcab279fba11f2f4fe9c14

Observation f3706b0f-9452-4ba3-a236-bce2058023bb · outbound

This paper cites Towards system 2 reasoning in llms: Learning how to think with meta chain-of-thought,.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Towards system 2 reasoning in llms: Learning how to think with meta chain-of-thought,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:43.550612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:41.140068Z digest=sha256:587b30c15b21a00d7331002c741f2e158371d06ee483384f363a75bf3ad7f6e2

Observation 5959e0aa-7424-4e59-9da2-53b1da599da6 · outbound

This paper cites Limitations.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Limitations

Reference 45

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T15:42:42.895189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:41.601093Z digest=sha256:69d264704da43bdb752822d78f8437d084f8a94675d76947dc49faeb4245268d

Observation 9a873439-7ef1-42fd-8bbd-3825ae6f777d · outbound

This paper cites Boosting conversational question answering with fine-grained retrieval-augmentation and self-check.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Boosting conversational question answering with fine-grained retrieval-augmentation and self-check

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:43.146750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:41.427031Z digest=sha256:f359d68ea81dfb2009695ed2f6cff5a750c44f75f8a57fedaf39f81df08da6fd

Observation fa825ad6-012a-4b6d-b0a1-d776e10aae85 · outbound

This paper cites 20 • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks 20 • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:42:42.737214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:41.769511Z digest=sha256:83ef7f8f37b5ef9dc9f7c5dccdcf45bed6f24fe6c0d4ed433a5c45d7259a8433

Observation 6d981240-12ea-42af-a874-8988038e7dae · outbound

This paper cites Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval Evaluation.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval Evaluation

Reference 2024

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:42:42.279027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T15:42:38.899569Z digest=sha256:d47d29897bd4288a95156d9da59dbe6a5df6899ca3e58acc429de81c79e4bc7c

Observation 1189bdc3-20cf-4933-abe3-eb27f0a95585 · outbound

This paper cites Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought.

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:41.245910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:41.245910Z digest=sha256:a32fc7ce385e0d2a6c9e5d4be5a1084defa23c693836162a81ff32c1865ef299

Pith citing papers

Observation eeaa444b-e0dc-4ac3-9ca2-7a2b5c0d1402 · inbound

A Benchmark Construction and Evaluation Framework for Specialist Domains: Case Study on Defense-related Documents cites this paper.

A Benchmark Construction and Evaluation Framework for Specialist Domains: Case Study on Defense-related Documents Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:30:19.560054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T04:51:28.638793Z digest=sha256:46b1917d5dcb0b2ab34719daf148bfd700b95f8e5e2d2d08742b1251f5ba4bd8

Observation d9a7987f-303e-4fd2-9401-33766b320323 · inbound

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA cites this paper.

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:45:42.820233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T05:07:58.441326Z digest=sha256:b42d0e892dd97e53720193e223f9ce6638cff7360fc5b86da82e1b2466fefbc9

Observation afd2a806-9d73-4379-9da8-64ad15f8d019 · inbound

GraphQAG: A Knowledge-Graph-Guided Visual Analytics Framework for Question-Answer Pairs Generation cites this paper.

GraphQAG: A Knowledge-Graph-Guided Visual Analytics Framework for Question-Answer Pairs Generation Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-30T11:07:25.667648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:07:25.667648Z digest=sha256:eb4d22a8f5505f7ff58f64f35ba15dba297fa276a40512ea22df4077a8583c75