Leveraging a dataset of paired narratives, we investigate the extent to which large language models (LLMs) can reliably separate incoherent and coherent stories...
In pre-market drug safety review, grouping related adverse event terms into standardised MedDRA queries or the FDA Office of New Drugs Custom Medical Queries (O...
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language understanding tasks. While these models often produce ling...
Online incivility has emerged as a widespread and persistent problem in digital communities, imposing substantial social and psychological burdens on users. Alt...
Large Language Models (LLMs) have demonstrated remarkable performance in code intelligence tasks such as code generation, summarization, and translation. Howeve...
Article URL: https://www.experimental-history.com/p/bag-of-words-have-mercy-on-us Comments URL: https://news.ycombinator.com/item?id=46185957 Points: 12 Comment...
The paper presents the formulation, implementation, and evaluation of the ArcGD optimiser. The evaluation is conducted initially on a non-convex benchmark funct...
The Problem: Why Standard RAG Fails The Vocabulary Mismatch Problem Imagine you've built a beautiful RAG system. You've indexed thousands of documents, created...
The Naive Approach Let’s be specific: for each timestep we want to see every character behind us in order to make our decision. A simple way is to carry the da...
In the era of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures are gaining significant attention for their ability to ground lan...
Vision-language models (VLMs) have achieved strong performance in visual question answering (VQA), yet they remain constrained by static training data. Retrieva...
Grounding is a fundamental capability for building graphical user interface (GUI) agents. Although existing approaches rely on large-scale bounding box supervis...
