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Paper Citation Record · LEDGER

ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2310.10996.

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

pith.paper-citation-record.v1
2310.10996 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:45:11.828761Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T03:17:00.751186Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0ba9f0df-e0c5-493f-a216-d70782c1dac3 · inbound

Towards Advancing Code Generation with Large Language Models: A Research Roadmap cites this paper.

Towards Advancing Code Generation with Large Language Models: A Research Roadmap ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T18:24:12.771099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:24:12.771099Z digest=sha256:301bbf89c0a85cb927909e829dea4f3929f70d22557d6eeac953c9e2a35b018b

Observation b06644e0-3114-4a59-a470-29c1310b49aa · inbound

CollabLLM: From Passive Responders to Active Collaborators cites this paper.

CollabLLM: From Passive Responders to Active Collaborators ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T18:18:09.226827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:18:09.226827Z digest=sha256:82d0934c3f305d921f6391d356201799f96162731d460cf0a04466a8b7e74496

Observation 4f6943a8-ebac-41b9-8204-0c5e37975662 · inbound

LLMCup: Ranking-Enhanced Comment Updating with LLMs cites this paper.

LLMCup: Ranking-Enhanced Comment Updating with LLMs ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T18:19:58.344485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:19:58.344485Z digest=sha256:69d698069aa16d85719f35b4f5f4003b7fad6ecde3e8417a0bd3ab096aade889

Observation b9a286c7-d5f7-46d5-8a7f-4c8c3e3de90f · inbound

Generating Project-Specific Test Cases with Requirement Validation Intention cites this paper.

Generating Project-Specific Test Cases with Requirement Validation Intention ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:17:00.754091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-19T03:15:10.410454Z digest=sha256:cb229badb4e72db4e56c0deef144e51f409db9cbcbd1805e43961503f69696d0

Observation 3ae6c88d-d3fb-4f83-8afe-0d25fd4b9437 · inbound

Generating Project-Specific Test Cases with Requirement Validation Intention cites this paper.

Generating Project-Specific Test Cases with Requirement Validation Intention ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T17:45:11.828761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:45:11.828761Z digest=sha256:096dc11621310d96b11bbef0c227c6af6b168a261387312a9900e20e34264afe

Observation 1f54dd5a-268a-4b3b-801e-cdab711ba8e6 · inbound

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation cites this paper.

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-05T21:48:02.743408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:48:02.743408Z digest=sha256:6a082438193edc274c2d72ee3b493533d6797a666880725d1f2b6a00e176022c

Observation 543c4a55-ec88-4fe5-b7a2-d92dc53fd069 · inbound

Generative Interfaces for Language Models cites this paper.

Generative Interfaces for Language Models ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:01:51.476776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T20:56:49.337356Z digest=sha256:b9a96c82dcbb2dce493d32f16746fcada017cf632a3922ea18b7bea8e7b8bf76

Observation f45bd011-ca57-47fa-ad98-e770bf4b4037 · inbound

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities cites this paper.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T10:30:40.825075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:30:40.825075Z digest=sha256:f3876dd2451c409c23277df6bd3c38a9f553c95116a206b5839ca385da2be2e3

Observation 143d730b-50f8-46b0-a0e2-22f9c9bef3f9 · inbound

Bridging the Gap between User Intent and LLM: A Requirement Alignment Approach for Code Generation cites this paper.

Bridging the Gap between User Intent and LLM: A Requirement Alignment Approach for Code Generation ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:17:37.620506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T08:13:43.804756Z digest=sha256:af1f116f05fb414dd9923a0884d88ef77caa332b20f2f0d2e39e7db70001c393

Observation f971e8f2-7d7e-499e-a2a5-efec4d7f07f2 · inbound

Obey, Diverge, Collapse: Blind Obedience to Incorrect Instructions Drives Code LLMs to Irrecoverable Code Semantic Collapse cites this paper.

Obey, Diverge, Collapse: Blind Obedience to Incorrect Instructions Drives Code LLMs to Irrecoverable Code Semantic Collapse ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-11T17:45:46.872944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T17:45:46.872944Z digest=sha256:a405013638883430cdf74040719b02219b915ebb915c6ffe2035257007564221