Paper Citation Record · LEDGER

Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2411.02382.

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

pith.paper-citation-record.v1
2411.02382 v1

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 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:35:44.296888Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:27:25.319615Z

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 3366b9f4-d3d3-4768-97c1-2312aa60d3c6 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 215

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:32:33.026458Z

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.

Observation 4567ab4b-5647-475f-9c88-b6b85dbfc96c · 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 Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T15:35:44.296888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fdc8173-864d-447b-9033-9030ba33c6ee · inbound

AI Scientists Fail Without Strong Implementation Capability cites this paper.

AI Scientists Fail Without Strong Implementation Capability Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:06.537534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54597817-6620-419a-bb2b-28ff9096612c · inbound

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior cites this paper.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:29.837731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c353b0f-37c0-4bd4-8737-b790a82e39fa · inbound

Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator cites this paper.

Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 198

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T05:17:06.289655Z

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.

Observation 4b3a0bc3-94d0-4a6f-9b7f-403f8fc7bc8e · inbound

Interestingness First Classifiers cites this paper.

Interestingness First Classifiers Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T15:33:46.443892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92e74c81-8f2c-4502-a5eb-4c72cc7311b2 · inbound

The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation? cites this paper.

The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation? Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T17:03:40.907143Z

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.

Observation 22bcf9b9-53f7-4878-b693-d4681691e245 · inbound

DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations cites this paper.

DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:27:25.321458Z

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.

Observation 17371a9a-1f9a-4be5-90ce-fd8979f94b4e · inbound

DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations cites this paper.

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T12:08:59.452879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dc938d4-e831-49b9-b41b-df57d32cea21 · inbound

ResearchStudio-Idea: An Evidence-Grounded Research-Ideation Skill Suite from ML Conference Outcomes cites this paper.

ResearchStudio-Idea: An Evidence-Grounded Research-Ideation Skill Suite from ML Conference Outcomes Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-11T19:11:37.739920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b409e85-f4f8-491b-a289-990b23499c12 · inbound

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation cites this paper.

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T23:25:06.598618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57aed704-e289-4494-8194-659823dd496f · inbound

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation cites this paper.

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:11.963054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.