1 code implementation • 11 Aug 2023 • Anisha Gunjal, Jihan Yin, Erhan Bas
We find that even the current state-of-the-art LVLMs (InstructBLIP) still contain a staggering 30 percent of the hallucinatory text in the form of non-existent objects, unfaithful descriptions, and inaccurate relationships.
no code implementations • 28 Apr 2023 • George Pu, Anirudh Jain, Jihan Yin, Russell Kaplan
As foundation models continue to exponentially scale in size, efficient methods of adaptation become increasingly critical.
no code implementations • ICLR 2021 • Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez
Machine learning applications such as finance and medicine demand accurate and justifiable predictions, barring most deep learning methods from use.
2 code implementations • 1 Apr 2020 • Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez
Machine learning applications such as finance and medicine demand accurate and justifiable predictions, barring most deep learning methods from use.