Large Language Models (LLMs) have shown remarkable capabilities in tool calling and tool usage, but suffer from hallucinations where they choose incorrect tools...
Pervasive AI increasingly depends on on-device learning systems that deliver low-latency and energy-efficient computation under strict resource constraints. Liq...
Stock market price prediction is a significant interdisciplinary research domain that depends at the intersection of finance, statistics, and economics. Forecas...
Large vision-language models (VLMs) are highly capable, yet often hallucinate by favoring textual prompts over visual evidence. We study this failure mode in a ...
In this study, we aim to better align fall risk prediction from the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) with additional clinically meaningful measu...
When researchers deploy large language models for autonomous tasks like reviewing literature or generating hypotheses, the computational bills add up quickly. A...
Large language models (LLMs) have revolutionized text-based code automation, but their potential in graph-oriented engineering workflows remains under-explored....
The rapid advancement of large language models (LLMs) has led to growing interest in using synthetic data to train future models. However, this creates a self-c...
Embodied question answering (EQA) in 3D environments often requires collecting context that is distributed across multiple viewpoints and partially occluded. Ho...
Large Language Models (LLMs) for complex reasoning is often hindered by high computational costs and latency, while resource-efficient Small Language Models (SL...
Article URL: https://epoch.ai/data-insights/us-vs-china-eci Comments URL: https://news.ycombinator.com/item?id=46543933 Points: 10 Comments: 5...
Don't miss our most popular articles of the previous month The post TDS Newsletter: December Must-Reads on GraphRAG, Data Contracts, and More appeared first on...
