Browsing: Hugging Face

Retrieval-augmented generation (RAG) is a common strategy to reduce hallucinations in Large Language Models (LLMs). While reinforcement learning (RL) can…

Designing biological sequences that satisfy multiple, often conflicting, functional and biophysical criteria remains a central challenge in biomolecule engineering. While…

As Large Language Models (LLMs) are increasingly applied to document-based tasks – such as document summarization, question answering, and information…

Recent developments in Large Language Models (LLMs) have shifted from pre-training scaling to post-training and test-time scaling. Across these developments,…

First Foundational and Conceptual Survey of VLAs Vision-Language-Action (VLA) models mark a transformative advancement in artificial intelligence, aiming to unify…

Robust and efficient local feature matching plays a crucial role in applications such as SLAM and visual localization for robotics.…

Contrastive Language-Image Pre-training (CLIP) excels in multimodal tasks such as image-text retrieval and zero-shot classification but struggles with fine-grained understanding…

Large language model (LLM) unlearning is critical in real-world applications where it is necessary to efficiently remove the influence of…

Aligning language models with human preferences relies on pairwise preference datasets. While some studies suggest that on-policy data consistently outperforms…

Chain-of-thoughts (CoT) requires large language models (LLMs) to generate intermediate steps before reaching the final answer, and has been proven…