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Paper Citation Record · LEDGER

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms

As of 18 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2412.02149.

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

pith.paper-citation-record.v1
2412.02149 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:50:13.197441Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy12
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5c34127-09a9-4e2b-beb3-2c679002eabe · outbound

This paper cites Longformer: The Long-Document Transformer.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Longformer: The Long-Document Transformer

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.134377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.134377Z digest=sha256:4dd04921bafa6804bd8c9c5ab666248381724998f52a94ec6f57c13ad110f98a

Observation ec4f4e23-6434-4738-b60b-2b5698029908 · outbound

This paper cites Big bird: Transformers for longer sequences.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Big bird: Transformers for longer sequences

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.137687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.137687Z digest=sha256:1d00b61758c60f1a9a7d41ad30f05085aaf321cc4e9f7bbf552eb26a14157a91

Observation 844c76aa-9d9b-4eab-a618-c436c6954638 · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Thread of Thought Unraveling Chaotic Contexts

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.140389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.140389Z digest=sha256:d61e61532880dfe7ebc784e175c4761286206661153192a212e33c09d098db32

Observation 48c3788b-8c98-4c26-b30a-5c45699c5bc0 · outbound

This paper cites Comparison of natural language processing tools for automatic gene ontology annotation of scientific literature.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Comparison of natural language processing tools for automatic gene ontology annotation of scientific literature

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.370077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.143309Z digest=sha256:2002d41fca4462b2c81b9bcc8394b20483387e9b2b18a8e5b6184e10fe2cc362

Observation a66dfa29-3dc3-4bd3-abba-00964515e124 · outbound

This paper cites Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.146176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.146176Z digest=sha256:3e3d42a3f2a98ce7ce63e0c1451faefd2106bfca69a540e1f5a292545f05b04c

Observation f6f98f8e-61e5-4cac-858b-76dbb2fb0932 · outbound

This paper cites Deep reinforcement and transfer learning for abstractive text summarization: A review.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Deep reinforcement and transfer learning for abstractive text summarization: A review

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.363153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.148940Z digest=sha256:ed8f399af35ed23841377cf9fb2d45bfdf39b6fbb33ed6bd68796befae705373

Observation a535c2fd-8da8-42ec-bd79-578cf1e07154 · outbound

This paper cites an unresolved cited work.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Unresolved cited work

Reference 8

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unresolved
no resolver link, observed 2026-08-11T23:50:13.154078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.154078Z digest=sha256:339fbac487d36a710766adbd992fc16b2bcc052bb7092726d8204ae1a52aae6b

Observation 785de478-9858-4666-b8fc-645528d96650 · outbound

This paper cites Longlora: Efficient fine-tuning of long-context large language models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Longlora: Efficient fine-tuning of long-context large language models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.355951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.156515Z digest=sha256:bd83c95b471684ca9335f69395643ce997b0fab3e7e517ddfe1d729ffe17bd48

Observation 88f62920-92a4-4986-bd5a-8ee2a6e1624f · outbound

This paper cites BAMBOO: A comprehensive benchmark for evaluating long text modeling capacities of large language models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms BAMBOO: A comprehensive benchmark for evaluating long text modeling capacities of large language models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.348536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.158834Z digest=sha256:404211509c58554d659fcd403205f662ebb61ad37c8dba502c82e28cb3b2bef4

Observation 59af87e7-f67d-425b-b1e1-7f7f989b6e21 · outbound

This paper cites Content Reduction, Surprisal and Information Density Estimation for Long Documents.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Content Reduction, Surprisal and Information Density Estimation for Long Documents

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-11T23:50:13.237057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.161247Z digest=sha256:58019c67aa522e5f194471502a2c76dd420056110d1c0dfde194cca38cac7cf4

Observation a16aa9e0-c8ef-463a-90c7-62298b8ca1f8 · outbound

This paper cites Retrieval meets long context large language models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Retrieval meets long context large language models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.341790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.163965Z digest=sha256:1bb4f6d67bc6f6a59c190267e0c8d68b2901815b901f680ac996788b7d1a5323

Observation 4320e4cc-d4db-4b02-89fa-07c440b1e1a1 · outbound

This paper cites Visual in-context learning for large vision-language models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Visual in-context learning for large vision-language models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.335854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.166485Z digest=sha256:8e72585e8c73b0978dec4ee4dac95a6e07d33ba931e83c3d22c9e95052b79859

Observation 9d410415-4c46-45a6-9302-a20af1d4c05f · outbound

This paper cites Claret: Pre-training a correlation-aware context-to-event transformer for event-centric generation and classification.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Claret: Pre-training a correlation-aware context-to-event transformer for event-centric generation and classification

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.329905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.168826Z digest=sha256:29a366cac7bc598ce8cad24bae86f20e05e37695661874af252b01a9053eea19

Observation c82cdb11-61a2-4dda-ba4c-847b4d63fb96 · outbound

This paper cites Eventbert: A pre-trained model for event correlation reasoning.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Eventbert: A pre-trained model for event correlation reasoning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.322444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.171101Z digest=sha256:93d9f915b087c55bcd400c78635fe527aeaa5be8af20ef90552a20b929b4d7fc

Observation cf937d97-5f95-45c6-9abc-2ac5d32d0489 · outbound

This paper cites Towards robust ranker for text retrieval.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Towards robust ranker for text retrieval

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.173438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.173438Z digest=sha256:a1c00f3687fd4e87458bf03aba698174e03a7924d75336884f7a0feba9698e54

Observation 68b30886-72f3-4249-925f-8a355461a8d2 · outbound

This paper cites Fine-grained distillation for long document retrieval.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Fine-grained distillation for long document retrieval

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.311040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.175654Z digest=sha256:49c2aee551958f40e781c483ae19b1022c4f91e6519fe52b36216f68295bb541

Observation 9b956de5-eee7-47aa-81f7-c005e9887ed5 · outbound

This paper cites ChatCite: LLM Agent with Human Workflow Guidance for Comparative Literature Summary.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms ChatCite: LLM Agent with Human Workflow Guidance for Comparative Literature Summary

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.177384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.177384Z digest=sha256:f60800919b465746ab0d36dba49304ccdf5a13910b48605b41f0d82995728c49

Observation 064cbf09-e611-4fce-aed9-c8bca8dc297e · outbound

This paper cites LitLLM: A Toolkit for Scientific Literature Review.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms LitLLM: A Toolkit for Scientific Literature Review

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.179802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.179802Z digest=sha256:c426e99aabe5345c325860b21dfab94972894fdc8199ab026e751ab24ed48369

Observation e47c251b-cdb5-40e9-8377-a9ad2daf11bb · outbound

This paper cites McKeown, and Tatsunori B.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms McKeown, and Tatsunori B

Reference 20

Resolution
malformed identifier
no resolver link, observed 2026-08-11T23:50:13.182003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.182003Z digest=sha256:e2b5b033c9c32684fdf94b86e8be043797f35730dc5779f794b120e2822b65e0

Observation 24a5ebc7-53c6-4e2c-9bd1-8ce61b33e251 · outbound

This paper cites an unresolved cited work.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-11T23:50:13.303496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.183789Z digest=sha256:ecab7b847bd5237534afafe02e3b43c5ee0623885954d5bc8cd7f8e6979ec30d

Observation f1a81557-149d-40a6-9313-8f2dc243107c · outbound

This paper cites Retrieval-augmented generation for code summarization via hybrid GNN.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Retrieval-augmented generation for code summarization via hybrid GNN

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.296508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 40f74dfe-1519-4f68-8cb2-000e650d2e9e · outbound

This paper cites Improving zero-shot cross-lingual transfer for multilingual question answering over knowledge graph.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Improving zero-shot cross-lingual transfer for multilingual question answering over knowledge graph

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.289126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.187476Z digest=sha256:17609c9ff529e70a8067da62b2b58c551d0e948f65ad9610126ef28163d89869

Observation d38f0ba7-c917-47bb-82fe-4c34d53fc9f0 · outbound

This paper cites Modeling event-pair relations in external knowledge graphs for script reasoning.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms Modeling event-pair relations in external knowledge graphs for script reasoning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:50:13.281693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T23:50:13.189374Z digest=sha256:0f77a115c5b6a620e1aa1045adb4cdb75f7877a409dbeffa6bca1b9babb221d2

Observation b1fca660-dcbf-40ce-a0a5-e30903206d0a · outbound

This paper cites The dawn after the dark: An empirical study on factuality hallucination in large language models.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms The dawn after the dark: An empirical study on factuality hallucination in large language models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.191800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.191800Z digest=sha256:e4c0ce7a6adeee0f029106cd25c6e2c250093a69e410725c1c5f4cfa7b2d0b16

Observation b3970738-4089-4f85-9f2f-990766bd395b · outbound

This paper cites URL: " 'urlintro :=.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms URL: " 'urlintro :=

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.194318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.194318Z digest=sha256:939148ee70063b4995fab3739206301526b3a9a606d2b93ce4a171373c9401b2

Observation 2be527b9-cef3-4b78-a120-a13982aaeb29 · outbound

This paper cites write newline.

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms write newline

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T23:50:13.197441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:50:13.197441Z digest=sha256:bc1c5559c957ed02cd525c9085dc0cf47a42ea6867a8f3cab7e02bcbe3be2d85

Pith citing papers

No inbound Pith citation observations are available.