activity
20192024
most citedHuggingFace's Transformers: State-of-the-art Natural Language Processing

3.1k citations · 3.2k across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 1 cited

Beyond Performance: Quantifying and Mitigating Label Bias in LLMs

Yuval Reif, Roy Schwartz

Large language models (LLMs) have shown remarkable adaptability to diverse tasks, by leveraging context prompts containing instructions, or minimal input-output examples. However,…

cs.CV2024

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…

cs.SE2024★ 67 cited

StarCoder 2 and The Stack v2: The Next Generation

Anton Lozhkov, Raymond Li, Loubna Ben Allal +63

The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…

cs.AI2023★ 11 cited

The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

Vipula Rawte, Swagata Chakraborty, Agnibh Pathak +5

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has paralle…

cs.CL2019★ 3.1k cited

HuggingFace's Transformers: State-of-the-art Natural Language Processing

Thomas Wolf, Lysandre Debut, Victor Sanh +19

Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building hig…