Geo-Strat-RL applies RLVR in a synthetic geological generator-verifier setup to boost VLM stratigraphic reasoning scores and shows transfer to synthetic seismic data without domain-specific training.
Geogalactica: A scientific large language model in geoscience
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 6verdicts
UNVERDICTED 6roles
background 1polarities
background 1representative citing papers
SIGA is a coding-agent adapter using retrieval, procedural memory, and validation gates that raises success rate on GEOS from 0.720 to 0.789 while cutting variance 16x and matching expert quality in minutes instead of hours.
GeoMind applies an agentic workflow with tool-augmented modules and process supervision to outperform static models on lithology classification from well logs while producing traceable decisions.
PETRA is a curated 1.36M-chunk petroleum-engineering retrieval dataset and pipeline that raises in-domain nDCG from 0.703 to 0.763 via score fusion and delivers 44% relative gain on an Earth Science benchmark through reranker adaptation on synthetic supervision.
HydroAgent fine-tunes Qwen3-4B on 2,576 expert calibration trajectories and applies Group-Relative Policy Optimization with NSE reward from live CREST simulations to improve hydrologic model calibration over frontier LLMs.
A review of Earth science foundation models covering capability evolution from perception to discovery, applications across atmosphere/hydrosphere/lithosphere/biosphere/anthroposphere/cryosphere, over 200 datasets, and key challenges.
citing papers explorer
-
Geo-Strat-RL: Learning Geological Event Reasoning from Verifiable Tasks
Geo-Strat-RL applies RLVR in a synthetic geological generator-verifier setup to boost VLM stratigraphic reasoning scores and shows transfer to synthetic seismic data without domain-specific training.
-
Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters
SIGA is a coding-agent adapter using retrieval, procedural memory, and validation gates that raises success rate on GEOS from 0.720 to 0.789 while cutting variance 16x and matching expert quality in minutes instead of hours.
-
GeoMind: An Agentic Workflow for Lithology Classification with Reasoned Tool Invocation
GeoMind applies an agentic workflow with tool-augmented modules and process supervision to outperform static models on lithology classification from well logs while producing traceable decisions.
-
PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation
PETRA is a curated 1.36M-chunk petroleum-engineering retrieval dataset and pipeline that raises in-domain nDCG from 0.703 to 0.763 via score fusion and delivers 44% relative gain on an Earth Science benchmark through reranker adaptation on synthetic supervision.
-
HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL
HydroAgent fine-tunes Qwen3-4B on 2,576 expert calibration trajectories and applies Group-Relative Policy Optimization with NSE reward from live CREST simulations to improve hydrologic model calibration over frontier LLMs.
-
Earth Science Foundation Models: From Perception to Reasoning and Discovery
A review of Earth science foundation models covering capability evolution from perception to discovery, applications across atmosphere/hydrosphere/lithosphere/biosphere/anthroposphere/cryosphere, over 200 datasets, and key challenges.