Earth Science Foundation Models: From Perception to Reasoning and Discovery | Paper Citation Record

Observation a6a0a895-5af5-4171-b27a-1bc54fa3bec8 · outbound

This paper cites Artificial intelligence for geoscience: Progress, challenges, and perspectives.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Artificial intelligence for geoscience: Progress, challenges, and perspectives

Reference 1

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Observation e766ca3a-9a83-4825-87c5-537f561624b8 · outbound

This paper cites Aurora: A foundation model of the atmosphere.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Aurora: A foundation model of the atmosphere

Reference 2

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This paper cites Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

Reference 3

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Observation 82bc0bdb-5a0c-4bf8-ad4c-2609951d2004 · outbound

This paper cites CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System.

Earth Science Foundation Models: From Perception to Reasoning and Discovery CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System

Reference 4

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Observation 93b40789-592c-43ba-a998-2cbddd9c9dd7 · outbound

This paper cites Graphcast: Ai model for faster and more accurate global weather forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Graphcast: Ai model for faster and more accurate global weather forecasting

Reference 5

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Observation 8bc210ef-0770-4985-8946-4c5d93064b96 · outbound

This paper cites S-clip: Semi-supervised vision-language learning using few specialist captions.

Earth Science Foundation Models: From Perception to Reasoning and Discovery S-clip: Semi-supervised vision-language learning using few specialist captions

Reference 6

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Observation f2e8924e-3d69-4961-a221-66b262d773d5 · outbound

This paper cites MarineDet: Towards Open-Marine Object Detection.

Earth Science Foundation Models: From Perception to Reasoning and Discovery MarineDet: Towards Open-Marine Object Detection

Reference 7

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Observation 4e77db43-d183-4291-a18d-7b58f5314ad7 · outbound

This paper cites Trs: Transformers for remote sensing scene classification.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Trs: Transformers for remote sensing scene classification

Reference 8

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Observation c43638bf-e6e7-4208-aa71-05b138bf8f84 · outbound

This paper cites Climateagents: A multi-agent research assis- tant for social-climate dynamics analysis.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Climateagents: A multi-agent research assis- tant for social-climate dynamics analysis

Reference 9

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Observation 038278fe-d9dc-4b3b-b019-77943a84588c · outbound

This paper cites OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents.

Earth Science Foundation Models: From Perception to Reasoning and Discovery OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents

Reference 10

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Observation 67326de8-0244-4bc0-ac74-b24177234ec5 · outbound

This paper cites Prithvi WxC: Foundation Model for Weather and Climate.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Prithvi WxC: Foundation Model for Weather and Climate

Reference 11

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Observation 72e6bd4d-0c6c-474a-bb62-3d4fb4a6c4d5 · outbound

This paper cites Terramind: Large-scale generative multimodality for earth ob- servation.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Terramind: Large-scale generative multimodality for earth ob- servation

Reference 12

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Observation 5046c3e4-3c9c-4609-9f52-8ee070bdd56e · outbound

This paper cites GISclaw: A Comprehensive Open-Source LLM Agent System for Realistic Multi-Step Geospatial Analysis.

Earth Science Foundation Models: From Perception to Reasoning and Discovery GISclaw: A Comprehensive Open-Source LLM Agent System for Realistic Multi-Step Geospatial Analysis

Reference 13

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Observation 2127d206-f82f-4122-b4f9-ddeb434ba2e1 · outbound

This paper cites Earthlink: A self-evolving ai agent for climate science.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Earthlink: A self-evolving ai agent for climate science

Reference 14

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Observation 4b48e2f9-f446-4f93-bc10-d9d57e9b0ddf · outbound

This paper cites Towards vision-language geo-foundation model: A survey.arXiv preprint arXiv:2406.09385, 2024a.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Towards vision-language geo-foundation model: A survey.arXiv preprint arXiv:2406.09385, 2024a

Reference 15

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Observation 84e6de1f-4fb7-43d9-821b-fa6e59324dbd · outbound

This paper cites Foundation models for remote sensing and earth observation: A survey.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Foundation models for remote sensing and earth observation: A survey

Reference 16

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Observation 673c8a69-87f9-4e1d-8411-35cf9f9d449c · outbound

This paper cites On the foundations of earth foundation models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery On the foundations of earth foundation models

Reference 17

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Observation fa378da4-e37d-48e5-8324-711d58a4d8bb · outbound

This paper cites A hierarchical multi-agent system for au- tonomous discovery in geoscientific data archives.

Earth Science Foundation Models: From Perception to Reasoning and Discovery A hierarchical multi-agent system for au- tonomous discovery in geoscientific data archives

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.176073Z

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Observation 39ce5dbf-576a-4bf5-bdf1-8b2d41f95627 · outbound

This paper cites Foun- dation models in remote sensing: Evolving from unimodality to multimodality.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Foun- dation models in remote sensing: Evolving from unimodality to multimodality

Reference 19

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Observation 0799cc0b-7c11-45cb-b5bc-1daf6777478b · outbound

This paper cites Towards urban general intelligence: A review and outlook of urban foundation models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Towards urban general intelligence: A review and outlook of urban foundation models

Reference 20

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Observation e84f2acd-84c3-4085-9836-e6bcf05fd635 · outbound

This paper cites Two-stream swin transformer with differentiable sobel operator for remote sensing image classification.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Two-stream swin transformer with differentiable sobel operator for remote sensing image classification

Reference 21

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Observation 59ad7f1c-3d4e-4a64-91c1-6db6bd830a17 · outbound

This paper cites Homo– heterogenous transformer learning framework for rs scene clas- sification.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Homo– heterogenous transformer learning framework for rs scene clas- sification

Reference 22

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Observation c5f8d48c-a2e6-412a-9e50-24558b200a8a · outbound

This paper cites Transformer with transfer cnn for remote-sensing-image object detection.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Transformer with transfer cnn for remote-sensing-image object detection

Reference 23

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Observation ebdc8c7c-5c5b-433f-9eec-dd24d5c5dc54 · outbound

This paper cites Gansformer: A detection network for aerial images with high performance com- bining convolutional network and transformer.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Gansformer: A detection network for aerial images with high performance com- bining convolutional network and transformer

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.357054Z

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Observation 40aa6e79-6bc3-4e20-a30d-8ccb564acdb6 · outbound

This paper cites Adt-det: Adaptive dynamic refined single-stage transformer detector for arbitrary- oriented object detection in satellite optical imagery.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Adt-det: Adaptive dynamic refined single-stage transformer detector for arbitrary- oriented object detection in satellite optical imagery

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.337632Z

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Observation 2fed6c2a-1670-4466-9100-aa6618ed837e · outbound

This paper cites Deep multiscale siamese network with parallel convolutional structure and self-attention for change detection.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Deep multiscale siamese network with parallel convolutional structure and self-attention for change detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.324853Z

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Observation d4acbd75-2625-4e24-8e51-f24048199074 · outbound

This paper cites Resdeepd: A residual super- resolution network for deep downscaling of daily precipitation over india.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Resdeepd: A residual super- resolution network for deep downscaling of daily precipitation over india

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.312619Z

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Observation e2d85c93-daa8-4f6e-902c-f441ada0b09d · outbound

This paper cites Downscal- ing multi-model climate projection ensembles with deep learning (deepesd): contribution to cordex eur-44.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Downscal- ing multi-model climate projection ensembles with deep learning (deepesd): contribution to cordex eur-44

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.314342Z

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Observation 46a1f22e-e563-4ec4-8af6-32da31d46aca · outbound

This paper cites Investigating two super-resolution methods for downscaling precipitation: ESRGAN and CAR.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Investigating two super-resolution methods for downscaling precipitation: ESRGAN and CAR

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.172808Z

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Observation 2775b6a5-9e33-45b9-97f8-e615639bcf9d · outbound

This paper cites Fast and accurate learned multiresolution dynamical downscaling for precipitation.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Fast and accurate learned multiresolution dynamical downscaling for precipitation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.319605Z

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Observation 7170ecbf-77c9-4a72-a1f5-857d5329cbd4 · outbound

This paper cites Adversarial super-resolution of climatological wind and solar data.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Adversarial super-resolution of climatological wind and solar data

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.307260Z

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Observation 378e5a86-461a-41c7-b900-45bdc87c8765 · outbound

This paper cites A deconvolution technology of microwave radiometer data using convolutional neural networks.

Earth Science Foundation Models: From Perception to Reasoning and Discovery A deconvolution technology of microwave radiometer data using convolutional neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.326671Z

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Observation cfcb2943-d9e7-40b8-acd9-c943ec1ac1cc · outbound

This paper cites Diffsr: Learning radar reflectivity synthesis via diffusion model from satellite observations.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Diffsr: Learning radar reflectivity synthesis via diffusion model from satellite observations

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.384028Z

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Observation 8c77ba86-fed5-46e6-a5bc-8d762c416064 · outbound

This paper cites Towards fine-grained classification of climate change related social media text.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Towards fine-grained classification of climate change related social media text

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.261082Z

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Observation c7350feb-ac3d-48ea-a642-146b8470ebda · outbound

This paper cites Few-shot learning for name entity recognition in geological text based on geobert.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Few-shot learning for name entity recognition in geological text based on geobert

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.409154Z

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Observation b26ce57f-f883-4376-8b6e-5cb13d3d30d5 · outbound

This paper cites An empirical study of remote sensing pretraining.

Earth Science Foundation Models: From Perception to Reasoning and Discovery An empirical study of remote sensing pretraining

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.255964Z

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Observation a953d5ca-cca0-4d0b-b698-7b6187cfefc3 · outbound

This paper cites EarthNets: Empowering AI in Earth Observation.

Earth Science Foundation Models: From Perception to Reasoning and Discovery EarthNets: Empowering AI in Earth Observation

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.143943Z

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Observation 8a792583-4814-491f-b0bf-019529e14c36 · outbound

This paper cites Anysat: One earth observation model for many resolutions, scales, and modalities.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Anysat: One earth observation model for many resolutions, scales, and modalities

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.410826Z

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Observation 2290b228-aa37-44e5-b4ad-8e54e22b7452 · outbound

This paper cites FlexiMo: A Flexible Remote Sensing Foundation Model.

Earth Science Foundation Models: From Perception to Reasoning and Discovery FlexiMo: A Flexible Remote Sensing Foundation Model

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.261084Z

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Observation 415b5078-8c89-468b-9d52-120ecfae3fc7 · outbound

This paper cites Spectralearth: Training hyperspectral foundation models at scale.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Spectralearth: Training hyperspectral foundation models at scale

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.296205Z

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Observation 365b50f6-2c49-4b7b-806f-5832998b6a4a · outbound

This paper cites DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation.

Earth Science Foundation Models: From Perception to Reasoning and Discovery DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.220132Z

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Observation 31c25338-c4c6-4d8c-90f3-9d9420b9bea9 · outbound

This paper cites Skysense: A multi-modal re- mote sensing foundation model towards universal interpretation for earth observation imagery.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Skysense: A multi-modal re- mote sensing foundation model towards universal interpretation for earth observation imagery

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.335649Z

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Observation 583a5df0-b95a-49cf-ad63-a0747199452f · outbound

This paper cites ClimaX: A foundation model for weather and climate.

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimaX: A foundation model for weather and climate

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:45.987728Z

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Observation 2eaabe1a-a99e-485b-97ce-53ae201b68cb · outbound

This paper cites WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning.

Earth Science Foundation Models: From Perception to Reasoning and Discovery WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.169697Z

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Observation 3fe169ea-8180-4d02-9b83-9ba554ab8264 · outbound

This paper cites Mmearth: Exploring multi-modal pretext tasks for geospatial representation learning.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Mmearth: Exploring multi-modal pretext tasks for geospatial representation learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:44.563883Z

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Observation f8758c97-c4bf-47e6-8c40-0242ac092438 · outbound

This paper cites CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding.

Earth Science Foundation Models: From Perception to Reasoning and Discovery CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:45.994220Z

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Observation 2c6167d1-17b4-4eaf-8630-fb53c981c59c · outbound

This paper cites EarthPT: a time series foundation model for Earth Observation.

Earth Science Foundation Models: From Perception to Reasoning and Discovery EarthPT: a time series foundation model for Earth Observation

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:45.978295Z

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Observation 7f0bd7e3-78ea-4e65-a1bd-f2f799685154 · outbound

This paper cites Bridging remote sensors with multisensor geospatial foundation models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Bridging remote sensors with multisensor geospatial foundation models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:44.637945Z

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Observation 0b5bb99f-b1fe-43b8-bfd3-c82f412c6e29 · outbound

This paper cites Mtp: Advancing remote sensing foundation model via multitask pretraining.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Mtp: Advancing remote sensing foundation model via multitask pretraining

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.437187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cbfc3871-c938-4ff1-b9b6-963f9d1f49a9 · outbound

This paper cites Spectraldiff: A generative framework for hyperspectral image classification with diffusion models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Spectraldiff: A generative framework for hyperspectral image classification with diffusion models

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.506671Z

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Observation 76daadb3-b990-474c-838d-bb0cc376d80f · outbound

This paper cites Geosynth: Contextually-aware high-resolution satellite image synthesis.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Geosynth: Contextually-aware high-resolution satellite image synthesis

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.477435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5ddfba78-49d4-42c8-bda3-a88933f1fd84 · outbound

This paper cites Diffusion-geo: A two-stage controllable text-to-image generative model for remote sensing scenarios.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Diffusion-geo: A two-stage controllable text-to-image generative model for remote sensing scenarios

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.460713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1242705a-70fd-475d-bc6d-863f857dba7f · outbound

This paper cites Toward artificial general intelligence in hydrogeolog- ical modeling with an integrated latent diffusion framework.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Toward artificial general intelligence in hydrogeolog- ical modeling with an integrated latent diffusion framework

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.472795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 54e40623-4db0-45b7-b294-56799aeab923 · outbound

This paper cites Tianxing: A linear complexity transformer model with explicit attention decay for global weather forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Tianxing: A linear complexity transformer model with explicit attention decay for global weather forecasting

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.541189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b3f91688-26fe-448e-a64a-7ad94e1eb680 · outbound

This paper cites ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.236214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3e987554-634a-4093-9b2d-73af4136ac1f · outbound

This paper cites OceanGPT: A Large Language Model for Ocean Science Tasks.

Earth Science Foundation Models: From Perception to Reasoning and Discovery OceanGPT: A Large Language Model for Ocean Science Tasks

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.156698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dac75b05-89ee-423d-8dfe-3a858b33b9eb · outbound

This paper cites K2: A foundation language model for geoscience knowledge understanding and utilization.

Earth Science Foundation Models: From Perception to Reasoning and Discovery K2: A foundation language model for geoscience knowledge understanding and utilization

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.512900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c811e899-47c2-4e9c-b394-c3319c77378f · outbound

This paper cites Jiuzhou: open foundation language models and effective pre-training 23 framework for geoscience.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Jiuzhou: open foundation language models and effective pre-training 23 framework for geoscience

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.433082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 98168105-d0ac-4347-aa1e-d27392c1b556 · outbound

This paper cites GeoGalactica: A Scientific Large Language Model in Geoscience.

Earth Science Foundation Models: From Perception to Reasoning and Discovery GeoGalactica: A Scientific Large Language Model in Geoscience

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.032423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3b5f2aea-caf7-486a-af9e-38cca43f2a5e · outbound

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

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.041840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f7dba0c0-ce68-4ac4-afe3-63ad7d94efb4 · outbound

This paper cites Geofactory: an llm performance enhancement framework for geoscience factual and inferential tasks.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Geofactory: an llm performance enhancement framework for geoscience factual and inferential tasks

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.456587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 482b0e13-f8af-422d-b620-c2f622371387 · outbound

This paper cites Lhrs-bot: Em- powering remote sensing with vgi-enhanced large multimodal language model.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Lhrs-bot: Em- powering remote sensing with vgi-enhanced large multimodal language model

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.501863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 21b28714-d104-4a97-bf3f-6eeda9257b1b · outbound

This paper cites SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding.

Earth Science Foundation Models: From Perception to Reasoning and Discovery SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.137194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0ea27c69-25c1-42c7-981c-0428290aaa5b · outbound

This paper cites Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.479428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5ca8402d-3f78-4444-a32a-50096d800727 · outbound

This paper cites Urbench: A comprehensive benchmark for evaluating large multimodal models in multi-view urban scenar- ios.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Urbench: A comprehensive benchmark for evaluating large multimodal models in multi-view urban scenar- ios

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.491387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7a11f5f7-d29c-4559-91d8-33e182fbb671 · outbound

This paper cites TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data.

Earth Science Foundation Models: From Perception to Reasoning and Discovery TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.071920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 87d351d8-6426-42e8-b624-e515516fdb90 · outbound

This paper cites Earthdial: Turning multi-sensory earth observations to interac- tive dialogues.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Earthdial: Turning multi-sensory earth observations to interac- tive dialogues

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.466184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a305c43f-cd57-43ba-9625-4cdea503b094 · outbound

This paper cites CLLMate: A Multimodal Benchmark for Weather and Climate Events Forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery CLLMate: A Multimodal Benchmark for Weather and Climate Events Forecasting

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.089446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9ce484e8-febd-4ed6-a2d8-e9323adaba0a · outbound

This paper cites Geochat: Grounded large vision-language model for remote sensing.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Geochat: Grounded large vision-language model for remote sensing

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.489665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1c4b5fe5-453d-4479-98dd-946f5f65f6ca · outbound

This paper cites Fuxi: a cascade machine learning forecasting system for 15-day global weather forecast.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Fuxi: a cascade machine learning forecasting system for 15-day global weather forecast

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.523099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 66397de1-dd98-4992-ac18-0aff0fbda561 · outbound

This paper cites Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.184651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7dedceb2-7c0f-4e4d-8803-18a53b51b780 · outbound

This paper cites W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.111826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 07535f84-3d0d-47c2-a995-cfe34dc9fdd2 · outbound

This paper cites Earthformer: Exploring space-time transformers for earth system forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Earthformer: Exploring space-time transformers for earth system forecasting

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.435229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a438ccca-9525-485c-a3d0-9c89e99fe5c0 · outbound

This paper cites Preformer: predictive transformer with multi-scale segment-wise correlations for long-term time series forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Preformer: predictive transformer with multi-scale segment-wise correlations for long-term time series forecasting

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.519002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 979414cd-24c6-44fc-aa19-fdd95e90dba2 · outbound

This paper cites Probabilistic weather forecasting with machine learning.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Probabilistic weather forecasting with machine learning

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.546737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd02c14e-45af-4d14-be3b-f4ee5a6e6556 · outbound

This paper cites Gen- erative emulation of weather forecast ensembles with diffusion models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Gen- erative emulation of weather forecast ensembles with diffusion models

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.544762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 519f2acd-a5c9-4a34-af94-6e8efabd8236 · outbound

This paper cites Continuous Ensemble Weather Forecasting with Diffusion models.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Continuous Ensemble Weather Forecasting with Diffusion models

Reference 77

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:46.016027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 43065fdc-496a-4a3f-873f-bf9f65a681a2 · outbound

This paper cites CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling.

Earth Science Foundation Models: From Perception to Reasoning and Discovery CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.117983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ca1fb67e-a71d-4965-b1a4-a8e5b2cb8a9f · outbound

This paper cites PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling.

Earth Science Foundation Models: From Perception to Reasoning and Discovery PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.147086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 24dbfdf0-9509-4324-8344-ab5572ac9821 · outbound

This paper cites Diffusion model with detail complement for super-resolution of remote sensing.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Diffusion model with detail complement for super-resolution of remote sensing

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.443413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa268037-1cb8-4753-8bff-d6605a654b32 · outbound

This paper cites Lds2ae: Local diffusion shared-specific autoencoder for multimodal remote sensing im- age classification with arbitrary missing modalities.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Lds2ae: Local diffusion shared-specific autoencoder for multimodal remote sensing im- age classification with arbitrary missing modalities

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.536195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 626394eb-b856-4a67-a6ff-b268095b1e30 · outbound

This paper cites Swimdiff: Scene- wide matching contrastive learning with diffusion constraint for remote sensing image.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Swimdiff: Scene- wide matching contrastive learning with diffusion constraint for remote sensing image

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.454415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d2c998a1-a9d7-45c1-b66e-7a0f4ec9771f · outbound

This paper cites Learning skillful medium-range global weather forecasting.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Learning skillful medium-range global weather forecasting

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.401881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 48968223-d6d5-462c-a247-24effb540f2a · outbound

This paper cites Forecasting Global Weather with Graph Neural Networks.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Forecasting Global Weather with Graph Neural Networks

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.105769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 816967e7-7c4f-4547-8f4c-ed9eb9f78e05 · outbound

This paper cites AIFS -- ECMWF's data-driven forecasting system.

Earth Science Foundation Models: From Perception to Reasoning and Discovery AIFS -- ECMWF's data-driven forecasting system

Reference 85

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:46.159831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f7ad75e8-f000-43d1-bbd2-c2e56c6aedb3 · outbound

This paper cites GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations.

Earth Science Foundation Models: From Perception to Reasoning and Discovery GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:46.059458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e908c3f5-855a-445d-9eb2-3318e964b11f · outbound

This paper cites Accelerating Earth Science Discovery via Multi-Agent LLM Systems.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Accelerating Earth Science Discovery via Multi-Agent LLM Systems

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.178834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 58a6ff9d-0c5a-4700-8074-9942d4d34ee6 · outbound

This paper cites Earth-agent: Unlocking the full landscape of earth observation with agents.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Earth-agent: Unlocking the full landscape of earth observation with agents

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.127611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 642d3255-92eb-455d-83d8-a33b38667ff9 · outbound

This paper cites An au- tonomous gis agent framework for geospatial data retrieval.

Earth Science Foundation Models: From Perception to Reasoning and Discovery An au- tonomous gis agent framework for geospatial data retrieval

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.405545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 47dfcb56-e721-4dd7-af7d-57c56f4ceb35 · outbound

This paper cites Intern-s1: A scientific multimodal foundation model.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Intern-s1: A scientific multimodal foundation model

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.102803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8b6d8b95-d7a6-46a9-8856-234dd5d421d5 · outbound

This paper cites One for all: Toward unified foundation models for earth vision.

Earth Science Foundation Models: From Perception to Reasoning and Discovery One for all: Toward unified foundation models for earth vision

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T12:03:45.531627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 45c213f4-40d9-40f4-b2c9-926aafb6ad01 · outbound

This paper cites A foundation model for the earth system.

Earth Science Foundation Models: From Perception to Reasoning and Discovery A foundation model for the earth system

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.371071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 202d3d5a-f929-441e-a90f-ffeeb34d30b1 · outbound

This paper cites Brain-inspired remote sensing foundation models and open problems: A comprehensive survey.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Brain-inspired remote sensing foundation models and open problems: A comprehensive survey

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.369255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7e93b708-2835-43ab-9f17-6039dc9bb820 · outbound

This paper cites Large remote sensing model: Progress and prospects.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Large remote sensing model: Progress and prospects

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.360461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fe67bdfa-6fac-4dfd-9931-b6f50a609370 · outbound

This paper cites Mak,Atmospheric dynamics.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Mak,Atmospheric dynamics

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.362172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 43dcc4bb-d19f-4f20-b211-bf38590f81dc · outbound

This paper cites Geology of mankind.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Geology of mankind

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.382081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 16b1026b-a2d0-4b53-a9a4-f407864ddedf · outbound

This paper cites Introduction to oceanography.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Introduction to oceanography

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:44.584935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e2b0490b-010e-4946-9727-d8ae7390d6b0 · outbound

This paper cites Climate change.

Earth Science Foundation Models: From Perception to Reasoning and Discovery Climate change

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:53:45.348282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2e3e907e-09b7-4e4e-805a-6ea1ec5df8dc · outbound

This paper cites CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims.

Earth Science Foundation Models: From Perception to Reasoning and Discovery CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims

Reference 99

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:46.099433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 21799b50-4335-43fc-bd79-022fa1808f06 · outbound

This paper cites ClimaText: A Dataset for Climate Change Topic Detection.

Earth Science Foundation Models: From Perception to Reasoning and Discovery ClimaText: A Dataset for Climate Change Topic Detection

Reference 100

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.080814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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