Paper Citation Record · LEDGER

Passage Segmentation of Documents for Extractive Question Answering

As of 11 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2501.09940.

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

pith.paper-citation-record.v1
2501.09940 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:35:12.306281Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

20 of 20 outbound references displayed

verified exact0
verified fuzzy0
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b64d802b-2876-4a38-ae61-c823d6dc7afb · outbound

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

Passage Segmentation of Documents for Extractive Question Answering Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.204481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ae877db-e5fd-42a9-ac67-3d1f89fbaf94 · outbound

This paper cites LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding.

Passage Segmentation of Documents for Extractive Question Answering LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.211766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 715db88c-5c10-4e5c-933a-fe129cc142c6 · outbound

This paper cites Dense X Retrieval: What Retrieval Granularity Should We Use?.

Passage Segmentation of Documents for Extractive Question Answering Dense X Retrieval: What Retrieval Granularity Should We Use?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.217576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d226de4a-24eb-406d-bfea-10c0b98fdc4a · outbound

This paper cites LumberChunker: Long-Form Narrative Document Segmentation.

Passage Segmentation of Documents for Extractive Question Answering LumberChunker: Long-Form Narrative Document Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.223623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38f224c4-edba-471c-b6fe-67fa6ca36731 · outbound

This paper cites The Llama 3 Herd of Models.

Passage Segmentation of Documents for Extractive Question Answering The Llama 3 Herd of Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.229563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3d58e89-6cfb-4c68-9c9c-2243274fc4a0 · outbound

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

Passage Segmentation of Documents for Extractive Question Answering Ragas: Automated Evaluation of Retrieval Augmented Generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.234751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1c3e87f-9a00-4c43-a3a4-2cf744749433 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Passage Segmentation of Documents for Extractive Question Answering Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.241301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cb1d968-3c17-463f-ae91-75c2adfa8390 · outbound

This paper cites an unresolved cited work.

Passage Segmentation of Documents for Extractive Question Answering Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:35:12.680414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 67f5ee02-1219-4956-993e-1a218409f881 · outbound

This paper cites an unresolved cited work.

Passage Segmentation of Documents for Extractive Question Answering Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:35:12.664782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 336194dd-9d20-42dc-b385-655a6494d41c · outbound

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

Passage Segmentation of Documents for Extractive Question Answering Dense Passage Retrieval for Open-Domain Question Answering

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.256063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4377d73f-26ba-4bc3-bad0-ad406f109523 · outbound

This paper cites The NarrativeQA Reading Comprehension Challenge.

Passage Segmentation of Documents for Extractive Question Answering The NarrativeQA Reading Comprehension Challenge

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.261501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00ff1ad-e0b0-4f7e-82ae-57d06cea8880 · outbound

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

Passage Segmentation of Documents for Extractive Question Answering Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.266508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed90c06a-981b-4b01-9e75-5ad0c59f0ab7 · outbound

This paper cites Grounding Language Model with Chunking-Free In-Context Retrieval.

Passage Segmentation of Documents for Extractive Question Answering Grounding Language Model with Chunking-Free In-Context Retrieval

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.271216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eca8d8bb-fc0e-4ff3-8865-36b4e8eb2456 · outbound

This paper cites an unresolved cited work.

Passage Segmentation of Documents for Extractive Question Answering Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:35:12.647652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7dae266d-d7e8-455d-8cbd-51e5d2a6b8b0 · outbound

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

Passage Segmentation of Documents for Extractive Question Answering Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.280388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89c841c3-1e41-48fd-bf86-25d694cad5c8 · outbound

This paper cites an unresolved cited work.

Passage Segmentation of Documents for Extractive Question Answering Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:35:12.630553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e466f848-5822-4512-be52-cada39e58a1a · outbound

This paper cites Learning to Filter Context for Retrieval-Augmented Generation.

Passage Segmentation of Documents for Extractive Question Answering Learning to Filter Context for Retrieval-Augmented Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.290614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bffa3500-acab-4a2f-9df3-76b8a820c532 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Passage Segmentation of Documents for Extractive Question Answering C-Pack: Packed Resources For General Chinese Embeddings

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.295893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 098482a7-8e2b-4336-ba51-12e3939152f0 · outbound

This paper cites an unresolved cited work.

Passage Segmentation of Documents for Extractive Question Answering Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:35:12.613577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2885e568-7fde-4e6c-8b33-9c741befccbd · outbound

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

Passage Segmentation of Documents for Extractive Question Answering RAFT: Adapting Language Model to Domain Specific RAG

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T19:35:12.306281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.