公开(公告)号：US20250124235A1

公开(公告)日：2025-04-17

申请号：US18485204

申请日：2023-10-11

Applicant: ADOBE INC.

Inventor： Victor Soares BURSZTYN ,  Xiang CHEN ,  Vaishnavi MUPPALA ,  Uttaran BHATTACHARYA ,  Tong YU ,  Saayan MITRA ,  Ryan ROSSI ,  Manas GARG ,  Kenneth George RUSSELL ,  Eunyee KOH ,  Alexandru Ionut HODOROGEA

IPC: G06F40/40 ,  G06F40/279

Abstract: Methods and systems are provided for using generative artificial intelligence to evaluate fine-tuned language models. In embodiments described herein, natural language text snippets are generated via a generative language model based on corresponding data. A language model is fine-tuned into a fine-tuned language model via a language model fine-tuning component using the natural language text snippets and the corresponding data as training data. Independent natural language text snippets are generated via the generative language model based on the corresponding data. Each independent natural language text snippet is different than each corresponding natural language text snippet. An evaluation metric of the fine-tuned language model is generated via an evaluation component based on the independent natural language text snippets and the corresponding data.

公开(公告)号：US20240163393A1

公开(公告)日：2024-05-16

申请号：US18055301

申请日：2022-11-14

Applicant: Adobe Inc.

Inventor： Uttaran BHATTACHARYA ,  Gang WU ,  Viswanathan SWAMINATHAN ,  Stefano PETRANGELI

IPC: H04N7/00 ,  G06T11/60

CPC classification number: H04N7/002 ,  G06T11/60

Abstract: Embodiments are disclosed for predicting, using neural networks, editing operations for application to a video sequence based on processing conversational messages by a video editing system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including a video sequence and text sentences, the text sentences describing a modification to the video sequence, mapping, by a first neural network content of the text sentences describing the modification to the video sequence to a candidate editing operation, processing, by a second neural network, the video sequence to predict parameter values for the candidate editing operation, and generating a modified video sequence by applying the candidate editing operation with the predicted parameter values to the video sequence.