Cover Image

Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hira, Kausik, Zaki, Mohd, Sheth, Dhruvil, Mausam, Krishnan, N M Anoop
Format:	Preprint
Published:	2023
Subjects:	Computation and Language Materials Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles
by: Gupta, Tanishq, et al.
Published: (2022)

MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables
by: Hira, Kausik, et al.
Published: (2025)

Foundational Large Language Models for Materials Research
by: Mishra, Vaibhav, et al.
Published: (2024)

Are LLMs Ready for Real-World Materials Discovery?
by: Miret, Santiago, et al.
Published: (2024)

Reliable End-to-End Material Information Extraction from the Literature with Source-Tracked Multi-Stage Large Language Models
by: Wang, Xin, et al.
Published: (2025)

Structured Extraction of Process Structure Properties Relationships in Materials Science
by: Verma, Amit K, et al.
Published: (2025)

Sampling Latent Material-Property Information From LLM-Derived Embedding Representations
by: Gilligan, Luke P. J., et al.
Published: (2024)

LLMs-Powered Accurate Extraction, Querying and Intelligent Management of Literature derived 2D Materials Data
by: Shang, Lijun, et al.
Published: (2025)

MaterialBENCH: Evaluating College-Level Materials Science Problem-Solving Abilities of Large Language Models
by: Yoshitake, Michiko, et al.
Published: (2024)

Automated Extraction of Material Properties using LLM-based AI Agents
by: Ghosh, Subham, et al.
Published: (2025)

NLP for Knowledge Discovery and Information Extraction from Energetics Corpora
by: VanGessel, Francis G., et al.
Published: (2024)

Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models
by: Polak, Maciej P., et al.
Published: (2023)

Materials science in the era of large language models: a perspective
by: Lei, Ge, et al.
Published: (2024)

Iterative Corpus Refinement for Materials Property Prediction Based on Scientific Texts
by: Zhang, Lei, et al.
Published: (2025)

LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction
by: Rubungo, Andre Niyongabo, et al.
Published: (2024)

Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering
by: Polak, Maciej P., et al.
Published: (2023)

MatTools: Benchmarking Large Language Models for Materials Science Tools
by: Liu, Siyu, et al.
Published: (2025)

Sustainable Materials Discovery in the Era of Artificial Intelligence
by: Mannan, Sajid, et al.
Published: (2026)

Autonomous Microscopy Experiments through Large Language Model Agents
by: Mandal, Indrajeet, et al.
Published: (2024)

LLMatDesign: Autonomous Materials Discovery with Large Language Models
by: Jia, Shuyi, et al.
Published: (2024)

MatExpert: Decomposing Materials Discovery by Mimicking Human Experts
by: Ding, Qianggang, et al.
Published: (2024)

Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery
by: Jia, Yunze, et al.
Published: (2025)

MaterialFigBENCH: benchmark dataset with figures for evaluating college-level materials science problem-solving abilities of multimodal large language models
by: Yoshitake, Michiko, et al.
Published: (2026)

Aligning Reasoning LLMs for Materials Discovery with Physics-aware Rejection Sampling
by: Hyun, Lee, et al.
Published: (2025)

Enhancing Large Language Models with Domain-Specific Knowledge: The Case in Topological Materials
by: Xu, HuangChao, et al.
Published: (2024)

Matter-of-Fact: A Benchmark for Verifying the Feasibility of Literature-Supported Claims in Materials Science
by: Jansen, Peter, et al.
Published: (2025)

AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials
by: Lv, Taoyuze, et al.
Published: (2025)

LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation
by: Chiang, Yuan, et al.
Published: (2024)

Toward Reliable Ad-hoc Scientific Information Extraction: A Case Study on Two Materials Datasets
by: Ghosh, Satanu, et al.
Published: (2024)

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model
by: Liu, Yuze, et al.
Published: (2025)

Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions
by: Wang, Hongchen, et al.
Published: (2024)

Generative Chemical Language Models for Energetic Materials Discovery
by: Salij, Andrew, et al.
Published: (2026)

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Functional Materials Discovery
by: Rothfarb, Samuel, et al.
Published: (2025)

Beyond Text and Tables: Vision-Language Model Integration in ComProScanner for Extracting Materials Data from Scientific Figures with High Accuracy
by: Roy, Aritra, et al.
Published: (2026)

Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property Prediction
by: Ekuma, Chinedu
Published: (2024)

Mapping Microstructure: Manifold Construction for Accelerated Materials Exploration
by: Mason, Simon A., et al.
Published: (2025)

A Decade of Generative Adversarial Networks for Porous Material Reconstruction
by: Sadeghkhani, Ali, et al.
Published: (2026)

The Northeast Materials Database for Magnetic Materials
by: Itani, Suman, et al.
Published: (2024)

Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials Analysis and Design
by: Buehler, Markus J.
Published: (2024)

Single and Multi-Hop Question-Answering Datasets for Reticular Chemistry with GPT-4-Turbo
by: Rampal, Nakul, et al.
Published: (2024)