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Paper Citation Record · LEDGER

Hypothesis Generation with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2404.04326.

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

pith.paper-citation-record.v1
2404.04326 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:35:44.319549Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:01:43.851635Z

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 dcecd143-52f7-4e3a-8f13-682e8c310db2 · inbound

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models cites this paper.

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models Hypothesis Generation with Large Language Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:44.319549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:44.319549Z digest=sha256:8f5ab2b7a2771b223c4feffa7e243effa968a064e395f0ec2a25177c6144e3c3

Observation f2467508-a0c2-463a-8fa8-d24f39eda3e9 · inbound

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification cites this paper.

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification Hypothesis Generation with Large Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:38.389609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:56:38.389609Z digest=sha256:630db40b29e59a85731b52e7808cc25a797c5dea985f91d30c6209430c7274f2

Observation 1551c4a8-e1f1-4d07-aca3-c1ceeaca247c · inbound

Correlated Errors in Large Language Models cites this paper.

Correlated Errors in Large Language Models Hypothesis Generation with Large Language Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T05:27:56.382686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:27:56.382686Z digest=sha256:3ba46ed77cb93d18f20a654df333afa5940eb22ec6280d279d1169e1a5935293

Observation 7f2868d2-774f-4c04-845a-285ed074ed81 · inbound

Formalizing Learning from Language Feedback with Provable Guarantees cites this paper.

Formalizing Learning from Language Feedback with Provable Guarantees Hypothesis Generation with Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T04:39:21.013047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:39:21.013047Z digest=sha256:561b913b84669aca2cd494c2dd8935bf3ce51eed397a07fa26fce5c9f9eefb2c

Observation 7949c3f4-1d09-460c-9acc-4774d8d5cddb · inbound

Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments cites this paper.

Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments Hypothesis Generation with Large Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:30:16.432138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:30:16.432138Z digest=sha256:cf0c90d45c6b8401b89bc4e43e224da010679cdb1f705ced0e7d8edb681867a8

Observation d0ac95e3-a8bc-4a7a-bfb7-5ae92995d5ee · inbound

Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers cites this paper.

Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers Hypothesis Generation with Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:00.074025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:29:00.074025Z digest=sha256:312d366753fe2e836ebccf0278396aa295bac1b0d9c1fa34bc1ec82d8ca0418d

Observation 87a32eb7-089c-40a5-b0f8-85786feeb8a2 · inbound

AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research cites this paper.

AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research Hypothesis Generation with Large Language Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T16:30:31.148470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:30:31.148470Z digest=sha256:1a64b17cb119eca7e3e792c15b0cdf185384628b685691db153b73a656ac4820

Observation d28be121-12b3-4086-bf72-a89b553c1aa7 · inbound

SciML Agents: Write the Solver, Not the Solution cites this paper.

SciML Agents: Write the Solver, Not the Solution Hypothesis Generation with Large Language Models

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:01:43.855020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T17:57:51.444493Z digest=sha256:c2de5c80ee2bbd7d76ab82930eda09d66d9c3c5d82a817c01f47565153128fcb

Observation 47605cc5-a09d-4012-b219-7b9e83b4d6ef · inbound

POPI: Personalizing LLMs via Optimized Natural Language Preference Inference cites this paper.

POPI: Personalizing LLMs via Optimized Natural Language Preference Inference Hypothesis Generation with Large Language Models

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:42:24.310651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T05:41:58.231139Z digest=sha256:6a890029489036e2db52b78e3acce9c5661eff822c24796d133046c04b83f340

Observation b530077d-2837-4026-910f-10659ba57d40 · inbound

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models cites this paper.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Hypothesis Generation with Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-04T08:39:45.342261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:39:45.342261Z digest=sha256:3392d8b71cf43911c2d0361a9173273b3169b871800c75b474357845fa2396c1

Observation 40c213ac-e26f-40fc-ac5c-bf3f17ddafdc · inbound

Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging cites this paper.

Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging Hypothesis Generation with Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-14T09:17:00.467000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T09:17:00.467000Z digest=sha256:006755095dd69c625fbdaf43df7faf8bb60655c778e63482bbeff65e0f72097b

Observation b2dbafac-21df-4894-a2f7-09566a748f61 · inbound

HALO: Interactive Co-abductive Reasoning in Scientific Hypothesis Generation cites this paper.

HALO: Interactive Co-abductive Reasoning in Scientific Hypothesis Generation Hypothesis Generation with Large Language Models

Reference 116

Resolution
unresolved
no resolver link, observed 2026-08-01T15:05:32.049278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:05:32.049278Z digest=sha256:988a2ebc5f95d653cf0cc37d6ef870e21eec11d749ae60d1772657560aa52467