Machine learning-guided protein engineering

P Kouba, P Kohout, F Haddadi, A Bushuiev… - ACS …, 2023‏ - ACS Publications
Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

KM Jablonka, Q Ai, A Al-Feghali, S Badhwar… - Digital discovery, 2023‏ - pubs.rsc.org
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists.
Recent studies suggested that these models could be useful in chemistry and materials …

Qwen technical report

J Bai, S Bai, Y Chu, Z Cui, K Dang, X Deng… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

Next-gpt: Any-to-any multimodal llm

S Wu, H Fei, L Qu, W Ji, TS Chua - Forty-first International …, 2024‏ - openreview.net
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides,
they mostly fall prey to the limitation of only input-side multimodal understanding, without the …

Multimodal foundation models: From specialists to general-purpose assistants

C Li, Z Gan, Z Yang, J Yang, L Li… - … and Trends® in …, 2024‏ - nowpublishers.com
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Dora: Weight-decomposed low-rank adaptation

SY Liu, CY Wang, H Yin, P Molchanov… - … on Machine Learning, 2024‏ - openreview.net
Among the widely used parameter-efficient fine-tuning (PEFT) methods, LoRA and its
variants have gained considerable popularity because of avoiding additional inference …

Llama-vid: An image is worth 2 tokens in large language models

Y Li, C Wang, J Jia - European Conference on Computer Vision, 2024‏ - Springer
In this work, we present a novel method to tackle the token generation challenge in Vision
Language Models (VLMs) for video and image understanding, called LLaMA-VID. Current …

On evaluating adversarial robustness of large vision-language models

Y Zhao, T Pang, C Du, X Yang, C Li… - Advances in …, 2023‏ - proceedings.neurips.cc
Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented
performance in response generation, especially with visual inputs, enabling more creative …

Shapellm: Universal 3d object understanding for embodied interaction

Z Qi, R Dong, S Zhang, H Geng, C Han, Z Ge… - … on Computer Vision, 2024‏ - Springer
This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

Instructeval: Towards holistic evaluation of instruction-tuned large language models

YK Chia, P Hong, L Bing, S Poria - arxiv preprint arxiv:2306.04757, 2023‏ - arxiv.org
Instruction-tuned large language models have revolutionized natural language processing
and have shown great potential in applications such as conversational agents. These …