The discovery of new materials is crucial to addressing pressing global challenges such as climate change and advancements in next-generation computing. However, existing computational and ...

Proteins, vital macromolecules, are characterized by their amino acid sequences, which dictate their three-dimensional structures and functions in living organisms. Effective generative protein ...

Alignment with human preferences has led to significant progress in producing honest, safe, and useful responses from Large Language Models (LLMs). Through this alignment process, the models are ...

Retrieval-Augmented Generation (RAG) is a growing area of research focused on improving the capabilities of large language models (LLMs) by incorporating external knowledge sources. This approach ...

In the rapidly evolving world of AI, challenges related to scalability, performance, and accessibility remain central to the efforts of research communities and open-source advocates. Issues such as ...

The growing reliance on large language models for coding support poses a significant problem: how best to assess real-world impact on programmer productivity? Current approaches, such as static ...

The rapid growth of large language models (LLMs) has brought impressive capabilities, but it has also highlighted significant challenges related to resource consumption and scalability. LLMs often ...

One of the most critical challenges of LLMs is how to align these models with human values and preferences, especially in generated texts. Most generated text outputs by models are inaccurate, biased, ...

Large language models (LLMs) have evolved to become powerful tools capable of understanding and responding to user instructions. Based on the transformer architecture, these models predict the next ...

Large language models (LLMs) have demonstrated consistent scaling laws, revealing a power-law relationship between pretraining performance and computational resources. This relationship, expressed as ...

The problem of over-optimization of likelihood in Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), arises when these methods ...

Training and deploying large-scale language models (LLMs) is complex, requiring significant computational resources, technical expertise, and access to high-performance infrastructure. These barriers ...