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Paper Citation Record · LEDGER

Large Language Models Meet NLP: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2405.12819.

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

pith.paper-citation-record.v1
2405.12819 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:30:40.903193Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

20
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1a02d7fa-3be3-44ea-98fc-5a1b6a1f249e · inbound

HintEval: A Comprehensive Framework for Hint Generation and Evaluation for Questions cites this paper.

HintEval: A Comprehensive Framework for Hint Generation and Evaluation for Questions Large Language Models Meet NLP: A Survey

Reference 78

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no resolver link, observed 2026-08-09T17:30:40.903193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:30:40.903193Z digest=sha256:5e28b4e2e2349e5c0e2355d3ab020c9fe0590a6f68f219d1bae1d5c4375678a0

Observation 969d7276-7cc1-4712-b903-b01ab00b9bc0 · inbound

Enhancing Phishing Email Identification with Large Language Models cites this paper.

Enhancing Phishing Email Identification with Large Language Models Large Language Models Meet NLP: A Survey

Reference 22

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no resolver link, observed 2026-08-08T21:38:52.550310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:38:52.550310Z digest=sha256:787515c8f686173cf372ab103abb20c2014647d9fdd4c35c1db7747c04987ae9

Observation 2273e93f-35bb-42aa-8ade-9c79b7ef0f06 · inbound

X-WebAgentBench: A Multilingual Interactive Web Benchmark for Evaluating Global Agentic System cites this paper.

X-WebAgentBench: A Multilingual Interactive Web Benchmark for Evaluating Global Agentic System Large Language Models Meet NLP: A Survey

Reference 28

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no resolver link, observed 2026-08-07T15:22:07.230593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:22:07.230593Z digest=sha256:38e6fc3a083c7fa4ccb761460dd4edf58a8b73080c872d0dc02c291ea29ca615

Observation 5bc0f881-f05d-463d-9898-a7630283a4ca · inbound

Analyzing Political Bias in LLMs via Target-Oriented Sentiment Classification cites this paper.

Analyzing Political Bias in LLMs via Target-Oriented Sentiment Classification Large Language Models Meet NLP: A Survey

Reference 33

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no resolver link, observed 2026-08-07T14:10:32.210050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:10:32.210050Z digest=sha256:cf3e2e1d73a905e058b8e37d5f37c4992ced1ffc9045bc20768d0574fc6b89c3

Observation 05ebf2ea-4de5-411c-ab2c-321cb5907307 · inbound

AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity cites this paper.

AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity Large Language Models Meet NLP: A Survey

Reference 18

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no resolver link, observed 2026-08-07T12:50:54.677876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:50:54.677876Z digest=sha256:c26a4e0a7ce6e88012508cd26cf9101e4981e46561e7188b64297d69a3ffae1d

Observation 91023965-ee3f-4a70-8f9e-7ffb3e946447 · inbound

An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3 cites this paper.

An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3 Large Language Models Meet NLP: A Survey

Reference 17

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no resolver link, observed 2026-08-07T12:12:49.917718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:49.917718Z digest=sha256:398f072e027458ff2a13c0772e8b230181386411dc991b69f47300471463e64c

Observation 9db97235-0370-412b-8814-37f8de908ba9 · inbound

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements cites this paper.

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements Large Language Models Meet NLP: A Survey

Reference 1

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no resolver link, observed 2026-08-07T04:35:42.184289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:35:42.184289Z digest=sha256:bb924c9149d033d097080d414078c3a5161a837e31708b05277f8766fe65f696

Observation 5b98f0a0-33cd-4afc-b40b-2d8e3fbbd78e · inbound

Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs cites this paper.

Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs Large Language Models Meet NLP: A Survey

Reference 90

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no resolver link, observed 2026-08-07T04:08:47.189430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:47.189430Z digest=sha256:8d02d3dcdb113b85eea27dc59ee84041475e787621c3f8a961c86fb3fd5530c7

Observation 96a7e48e-f2c5-4204-89ef-f57c109138f4 · inbound

MLDebugging: Towards Benchmarking Code Debugging Across Multi-Library Scenarios cites this paper.

MLDebugging: Towards Benchmarking Code Debugging Across Multi-Library Scenarios Large Language Models Meet NLP: A Survey

Reference 30

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no resolver link, observed 2026-08-07T00:42:09.550384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:42:09.550384Z digest=sha256:bed84f7f703f12c2cef1495a99cbb1a4d08d18ac7408e2f3df97cf1b6bf4e5b6

Observation 8f5a3dfb-fe81-4984-a699-8009d92c7ac0 · inbound

ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models cites this paper.

ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models Large Language Models Meet NLP: A Survey

Reference 26

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no resolver link, observed 2026-08-06T17:49:34.825536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:49:34.825536Z digest=sha256:5b3afdf1d30347f12547c3eb771366b57825253a768c50d4b2249fec1f81dbd7

Observation c1e4e7de-05f1-4953-9262-f453dc3f32cd · inbound

Real-World Summarization: When Evaluation Reaches Its Limits cites this paper.

Real-World Summarization: When Evaluation Reaches Its Limits Large Language Models Meet NLP: A Survey

Reference 20

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no resolver link, observed 2026-08-06T17:10:30.110514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:10:30.110514Z digest=sha256:946297faa7acdf271bbf83989a819e59083c615a86a4317dafc0f95077a1eafe

Observation 9b421890-e4de-40d8-bd6b-c54914423f29 · inbound

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection cites this paper.

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection Large Language Models Meet NLP: A Survey

Reference 21

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no resolver link, observed 2026-08-06T16:19:02.134995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:19:02.134995Z digest=sha256:44581accba38ef5997676110e5c6f6e965dedc42917798554dfe9ff6f52adc37

Observation 0e192c90-f314-4baf-97c2-5421a626f6b5 · inbound

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Large Language Models Meet NLP: A Survey

Reference 37

Resolution
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no resolver link, observed 2026-08-05T15:52:45.016364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.016364Z digest=sha256:7ef815eb15f309830882610076fe966e6a06adfc572ebee038255dbf73b908a1

Observation 5e05ef1c-8c22-4bdf-aabc-5339e41f32fd · inbound

Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning cites this paper.

Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning Large Language Models Meet NLP: A Survey

Reference 26

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no resolver link, observed 2026-08-05T15:29:57.404111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:29:57.404111Z digest=sha256:bb248938a246fb194209477738c076702b10943f77382767dbd2e7f941939525

Observation a3c743bb-61f6-4e56-9bbe-68086e6d8572 · inbound

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning cites this paper.

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning Large Language Models Meet NLP: A Survey

Reference 9

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no resolver link, observed 2026-08-05T13:46:02.642782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:46:02.642782Z digest=sha256:3d26ffe1e9050da4d35711c3d3a7215361034957c445bbad0a842d5f402b7fcc

Observation 7991ae40-1070-4654-8352-09934d3b8d26 · inbound

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI cites this paper.

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI Large Language Models Meet NLP: A Survey

Reference 6

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no resolver link, observed 2026-08-02T11:29:17.253862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:29:17.253862Z digest=sha256:f1da0efcb6c3228225a3c86dc018ed1bc795add172143af184595fe1ddfb990b

Observation 475603da-15bb-46a5-80e4-c37f94ea94c4 · inbound

Quantifying Political Partisanship for Cross-Platform Analyses cites this paper.

Quantifying Political Partisanship for Cross-Platform Analyses Large Language Models Meet NLP: A Survey

Reference 32

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metadata mismatch
local_arxiv, observed 2026-08-01T06:38:57.270141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-01T06:35:54.903537Z digest=sha256:8ce0642bbef7fdddeb37f1c16ef9c8711f7c4cf461a4d4590ec13e1e0e30aef0