2.3k citations · 2.7k across the 14 of their papers we have counts for
4 papers · 1 filter
Benchmarking Multi-Domain Active Learning on Image Classification
Jiayi Li, Rohan Taori, Tatsunori B. Hashimoto
Active learning aims to enhance model performance by strategically labeling informative data points. While extensively studied, its effectiveness on large-scale, real-world dataset…
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…
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use
Yonatan Bitton, Hritik Bansal, Jack Hessel +6
We introduce VisIT-Bench (Visual InsTruction Benchmark), a benchmark for evaluation of instruction-following vision-language models for real-world use. Our starting point is curati…
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
Yann Dubois, Xuechen Li, Rohan Taori +6
Large language models (LLMs) such as ChatGPT have seen widespread adoption due to their strong instruction-following abilities. Developing these LLMs involves a complex yet poorly…