Pith. sign in

Paper Citation Record · LEDGER

ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.09646.

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

pith.paper-citation-record.v1
2401.09646 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:30:57.644059Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:58.950716Z

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 58d1e38d-766e-4c5c-8c34-fe803e6f2433 · inbound

Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change cites this paper.

Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:57.644059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:57.644059Z digest=sha256:49dcf48c285642fb482330952e692edeecf9101d917a7fca632589dc3bea8a69

Observation 964e3781-1e6e-4ced-94f8-b6ed99da58fd · inbound

The Curious Language Model: Strategic Test-Time Information Acquisition cites this paper.

The Curious Language Model: Strategic Test-Time Information Acquisition ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 1948

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:46.799251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:46.799251Z digest=sha256:425d277ac5fb510ee7adef587cd25bdde5258671d2e4d3f0700250baf6434318

Observation 82c9956c-b4f6-4b5d-89ae-683586cf9701 · inbound

ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries cites this paper.

ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T04:29:09.130624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:29:09.130624Z digest=sha256:5649d38bd775301d574ea3b6b7fc48f7d05a5332c136d3c504b0b311bf9c83c4

Observation 0a17ae5a-3e88-4ca2-b67b-376706694d28 · inbound

Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications cites this paper.

Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 163

Resolution
unresolved
no resolver link, observed 2026-08-06T21:07:11.221449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:07:11.221449Z digest=sha256:1df42bc8f41bf5409315ecbfee36a71668c4e639034a359c83f84de96f81fade

Observation 1022bb82-436a-437b-8384-e353d60d9b9f · inbound

Multi-Agent Visual-Language Reasoning for Comprehensive Highway Scene Understanding cites this paper.

Multi-Agent Visual-Language Reasoning for Comprehensive Highway Scene Understanding ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T17:03:30.097200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:03:30.097200Z digest=sha256:b8a4553124df9e902a50107bc498c96ebd80318b719550c36d433d77cd077d57

Observation 5345b789-74fe-4312-9917-349d3a4e5552 · inbound

A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn't) cites this paper.

A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn't) ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-02T23:11:04.246892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T23:11:04.246892Z digest=sha256:b80e4f1b72070419d31b2ae22e11daf86d2f05bfaac1b51041edc0c0ae3206bc

Observation 8044da20-14c9-4d52-817c-2844a497ccf4 · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 168

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:08:03.328349Z

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=2026-05-14T22:07:40.242567Z digest=sha256:7b9c07a6ac359ae001eca760da451da488fd22d0f0ccd391c73df7c3c2b6106a

Observation f9000215-123a-4102-93e2-78ca7114de9f · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 168

Resolution
verified exact
arxiv_id, observed 2026-07-01T13:35:46.114853Z

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=2026-06-30T23:07:21.558834Z digest=sha256:c8e17f6195a3e0240fde9584b29ca9966f0317a9d222f2c2dff109d4831165f2

Observation 5d6b0b33-00ee-4717-85ff-40f87cee6516 · inbound

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL cites this paper.

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:28:18.860392Z

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=arxiv_source observed=2026-05-20T13:28:03.965754Z digest=sha256:1c499e408992f581c699ed497a5cbb09c6e55937c9bfbf23a51d8cb7ca677f63

Observation b6904728-1726-40cd-b7c5-e6e57346d962 · inbound

CMIP-Forge: An Agentic System that Retrieves, Computes, and Self-Reviews Climate Science cites this paper.

CMIP-Forge: An Agentic System that Retrieves, Computes, and Self-Reviews Climate Science ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:48:21.120832Z

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=arxiv_source observed=2026-06-27T07:31:22.819171Z digest=sha256:7a89435c746cbd9c525c6ef295fd0b2ebfbb1e2e7e19b2ebb4ab8af8b2e2383b

Observation a5ced449-181c-4393-92c0-67348439eca1 · inbound

Task Decomposition for Efficient Annotation cites this paper.

Task Decomposition for Efficient Annotation ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change

Reference 230

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:59:58.952159Z

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=arxiv_source observed=2026-06-26T00:00:16.588823Z digest=sha256:c668dfd4e272dd896cefcbb8c3ab3503ddbc90bbed94df16e4525de3a72d5356