Paper Citation Record · LEDGER

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities

As of 11 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2507.08425.

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

pith.paper-citation-record.v1
2507.08425 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:24:51.214552Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T06:05:57.027679Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy1
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e97265a-3691-4e98-833a-631dfc265e26 · outbound

This paper cites From Generalist to Specialist: A Survey of Large Language Models for Chemistry.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities From Generalist to Specialist: A Survey of Large Language Models for Chemistry

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T18:24:51.444403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation db9cc37b-0dbd-4b49-ab1d-17d2a63bd56d · outbound

This paper cites CRISPR-GPT for Agentic Automation of Gene-editing Experiments.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities CRISPR-GPT for Agentic Automation of Gene-editing Experiments

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.388530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa5932ae-103b-408f-8310-c29d686ef438 · outbound

This paper cites OpenAI o1 System Card.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities OpenAI o1 System Card

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.463144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8dc4331-7409-47eb-aed5-2db0330d5194 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.691776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1123c35-e7ea-4409-abd2-544ecb87cd5d · outbound

This paper cites Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.745932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c272cd5d-6371-4d41-b9ee-39ecfea18ff8 · outbound

This paper cites SimPO: Simple Preference Optimization with a Reference-Free Reward.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities SimPO: Simple Preference Optimization with a Reference-Free Reward

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.818055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc81ebb3-afa9-48e5-a41a-78446c73c327 · outbound

This paper cites GPT-4 Technical Report.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities GPT-4 Technical Report

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.913898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9286d103-bc29-4828-9af2-1a705d815278 · outbound

This paper cites Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.006055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 607ac538-9352-468e-b459-326b1e56a9ba · outbound

This paper cites Research Notes of the AAS, 8(1):7.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Research Notes of the AAS, 8(1):7

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:51.568166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d6db9c54-1960-4a66-8d19-7edbaf9f91b6 · outbound

This paper cites The Political Preferences of LLMs.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities The Political Preferences of LLMs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.121279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03d0183e-4df4-44e7-b58b-69cd6957f88d · outbound

This paper cites HistoLens: An LLM-Powered Framework for Multi-Layered Analysis of Historical Texts -- A Case Application of Yantie Lun.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities HistoLens: An LLM-Powered Framework for Multi-Layered Analysis of Historical Texts -- A Case Application of Yantie Lun

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.214552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec71e065-5f11-4bc0-b7ce-101d49f8beeb · outbound

This paper cites CulturePark: Boosting Cross-cultural Understanding in Large Language Models.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities CulturePark: Boosting Cross-cultural Understanding in Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.577133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a11af68-0efc-4be6-a74d-e1e62d1df60c · outbound

This paper cites Llemma: An Open Language Model For Mathematics.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Llemma: An Open Language Model For Mathematics

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:26.404503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94911d3b-afb7-4106-97f8-76f5207560e9 · outbound

This paper cites Harnessing the Power of Adversarial Prompting and Large Language Models for Robust Hypothesis Generation in Astronomy.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Harnessing the Power of Adversarial Prompting and Large Language Models for Robust Hypothesis Generation in Astronomy

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:26.555669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f7bc17e-7a29-4add-b864-771090148c8a · outbound

This paper cites Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis.

A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:26.482405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7bd55e0c-8d90-4bf8-9b89-3332c8fa6972 · inbound

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs cites this paper.

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-01T06:05:57.027679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.