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Paper Citation Record · LEDGER

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2607.26891.

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

pith.paper-citation-record.v1
2607.26891 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T17:59:32.553795Z

measured 29 of 29 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T17:59:29.952523Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved25
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86371a40-9036-4a0b-9f26-ebecef0ef864 · outbound

This paper cites It is crucial for other downstream natural language processing (NLP) tasks, such as co-reference resolution [1], knowledge graph [2], and question gen- eration [3].

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models It is crucial for other downstream natural language processing (NLP) tasks, such as co-reference resolution [1], knowledge graph [2], and question gen- eration [3]

Reference 1

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Observation 466f07b4-7953-4fe1-8991-ce757d5634cf · outbound

This paper cites DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models

Reference 2

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Observation 79f585b7-0bc7-44fb-a21f-fba558c81951 · outbound

This paper cites Experimental Setup DatasetsWe evaluate the performance of our model on six NER datasets and two POS datasets.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Experimental Setup DatasetsWe evaluate the performance of our model on six NER datasets and two POS datasets

Reference 3

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Observation 0f66b593-4959-4b8d-883e-d056aed9ff84 · outbound

This paper cites an unresolved cited work.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Unresolved cited work

Reference 4

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source=pdf_text observed=2026-07-30T17:59:30.204481Z digest=sha256:7ac405d32e0250283402057c6d45c21d417b482a0b484d17b6a73676ea923e1d

Observation 483c373f-e2ee-43ac-bff2-3fdbf0592bd7 · outbound

This paper cites Chain-of- thought prompting elicits reasoning in large language models,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Chain-of- thought prompting elicits reasoning in large language models,

Reference 5

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Observation 17908ee2-4606-4bf5-acd9-114781ef3aad · outbound

This paper cites Improving coref- erence resolution by learning entity-level distributed represen- tations,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Improving coref- erence resolution by learning entity-level distributed represen- tations,

Reference 6

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Observation 9334f34c-f15e-45b9-8736-158ade4453bf · outbound

This paper cites A survey on knowledge graphs: Representation, acquisition, and applications,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models A survey on knowledge graphs: Representation, acquisition, and applications,

Reference 7

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Observation 6e82f742-1da1-4330-951a-44d3bd6f00af · outbound

This paper cites Boosting low-resource biomedical qa via entity- aware masking strategies,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Boosting low-resource biomedical qa via entity- aware masking strategies,

Reference 8

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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.

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Observation 75bd5b38-84f3-4be2-a289-ce9dc85d80fc · outbound

This paper cites Training language models to follow instructions with human feedback,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Training language models to follow instructions with human feedback,

Reference 9

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Observation dc47ee55-1d74-41b9-8dcd-127695ce0d3b · outbound

This paper cites Rethinking Negative Instances for Generative Named Entity Recognition.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Rethinking Negative Instances for Generative Named Entity Recognition

Reference 10

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Observation 32896a99-786d-440b-a0ac-e79f9f73f684 · outbound

This paper cites Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP Education.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP Education

Reference 11

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Observation 9fbc7905-5db0-45b1-b8ea-f1640eb5f219 · outbound

This paper cites Unified Structure Generation for Universal Information Extraction.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Unified Structure Generation for Universal Information Extraction

Reference 12

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Observation a4158534-6023-4746-a6a7-33297dd5c14a · outbound

This paper cites Universal information extraction as unified semantic matching,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Universal information extraction as unified semantic matching,

Reference 13

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Observation 02f9a4b8-73ac-4bfc-b6e2-0262230d3d25 · outbound

This paper cites InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction

Reference 14

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Observation 8fabce84-5a61-49f6-a661-703d544acd73 · outbound

This paper cites Better modeling of incomplete annotations for named en- tity recognition,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Better modeling of incomplete annotations for named en- tity recognition,

Reference 15

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Observation 15469279-b0ef-4561-8191-aa273e953cb5 · outbound

This paper cites GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction

Reference 16

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Observation 352f91bb-1f0a-494e-bc32-7e23c11dded1 · outbound

This paper cites C-ICL: Contrastive In-context Learning for Information Extraction.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models C-ICL: Contrastive In-context Learning for Information Extraction

Reference 17

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Observation d9636227-fa47-4765-9120-9378664eed36 · outbound

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

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Bleu: a method for automatic evaluation of machine translation,

Reference 18

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Observation ef3a09a4-3548-4943-8715-030aac13f43d · outbound

This paper cites Named entity recogni- tion for chinese social media with jointly trained embed- dings,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Named entity recogni- tion for chinese social media with jointly trained embed- dings,

Reference 19

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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.

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Observation c890263e-c5f0-4501-b9ee-63559a506dfa · outbound

This paper cites The penn chinese treebank: Phrase structure annotation of a large corpus,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models The penn chinese treebank: Phrase structure annotation of a large corpus,

Reference 20

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Observation e7ddf7c9-e217-4520-b375-2c409eb13583 · outbound

This paper cites Chinese NER Using Lattice LSTM.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Chinese NER Using Lattice LSTM

Reference 21

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Observation 288af4ad-9afb-4842-b5c6-fa1cc78ffb02 · outbound

This paper cites Asgard: A portable architecture for multilingual dialogue sys- tems,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Asgard: A portable architecture for multilingual dialogue sys- tems,

Reference 22

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Observation b49d6aa9-0c2a-4a0e-aff1-6f5ad33cd2fb · outbound

This paper cites Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition

Reference 23

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Observation 3dfbf3f6-8f08-4edd-a5d5-2ca68e9c5585 · outbound

This paper cites Universal dependencies v1: A multilingual treebank collec- tion,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Universal dependencies v1: A multilingual treebank collec- tion,

Reference 24

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Observation d0248595-7df4-476c-b9bd-6d14a8e98201 · outbound

This paper cites The llama 3 herd of models,.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models The llama 3 herd of models,

Reference 26

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Observation 917fc075-7358-432b-afb5-4d4309ec7659 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 27

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Observation 4f9568b7-67dd-4ed2-9150-9a81991d3ef0 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models mT5: A massively multilingual pre-trained text-to-text transformer

Reference 28

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Observation 984c835a-a567-4b48-b77a-5ed8e749785d · outbound

This paper cites PLOT” entity or the “MISC.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models PLOT” entity or the “MISC

Reference 1000

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Pith citing papers

Observation 466f07b4-7953-4fe1-8991-ce757d5634cf · inbound

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models cites this paper.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models

Reference 2

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