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An original InternLM projectUpdated Nov 6 18:14

InternLM Open-Sources Sage-SciPerception (ShuSheng·YuanZheng): Connecting Scientific Encoders to Language Models

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InternLM has open-sourced Sage-SciPerception (ShuSheng·YuanZheng), which maps scientific encoders such as molecular graphs, spectra, crystal structures, protein and nucleic acid sequences into the language model input space through a trainable projector, and trains them separately by task. On QM9S joint spectral-structure recognition, Acc@1 is 49.75%; on BEACON ncRNA family classification, accuracy is 97.35%; and on JARVIS-DFT formation energy prediction, MAD/MAE is 15.03. The project provides three demos, and the projector checkpoint will be released on Hugging Face.

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Sage-SciPerception

Sage Sci Perception · Shusheng·Yuanzheng

Scientific perception for language models.

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🤗 Models · GitHub · Demos · Results

Introduction

Sage Sci Perception (Shusheng·Yuanzheng) connects scientific encoders to a language model through trainable projectors. It maps molecular graphs, spectra, crystal structures, protein and nucleic-acid sequences, and scientific signals into the language model's input space, enabling natural-language analysis and structured scientific answers. Projectors are trained for each task.

Framework

Demos

Three spectra → molecular structure

IR, Raman and UV–Vis with streamed analysis and a recorded prediction.

Protein interface sites

Sequence positions and reference residue-level annotations.

Crystal structure and formation energy

Atomic geometry and a reference material property.

RNA interface refinement

Design revisions guided by experimental feedback.

Results

Selected results from task-specific checkpoints, evaluated on generated answers.

Benchmark Task Metric ↑ Score

QM9S Joint-spectrum structure identification Acc@1 (%) 49.75

JARVIS-DFT Formation-energy prediction MAD/MAE 15.03

MPBind, assembly-1 reconstruction PPI interface sites Mean per-protein F1 (%) 61.12

SciTS PHU01 ECG classification Macro-F1 (%) 71.53

SciTS NEU06 Sleep staging Macro-F1 (%) 72.01

BEACON ncRNA RNA family classification Accuracy (%) 97.35

Projector checkpoints will be available on Hugging Face.

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Source

An original InternLM project