01 Nov -- 30 Nov, 2022
Last Week’s Work Review for the last month we found out that the agent had the following issues it gives more weights to the object detection than action detection, thus it gave wrong rewards when the agent was close to the target object but did the wrong action e.g., it gave high rewards for sentence “climb down the ladder” when the agent was staying on the ladder it tried to analyse each single word instead of recognising the phrases and the qualifier e.g., it gave rewards for sentence “go to the ladder on the right” when the agent was at the ladder on the middle e.g., it gave reward for sentence “climb down the ladder on the right” when the agent was jumping to the right platform the module cannot correctly handle the phrase “the ladder on the right”, instead, it treated it as two things – “ladder” and “right” our solution is to generate hard negative examples by replacing the noun phrase and the verb phrase in the original sentence with random phrases picked from the phrase set. and I call it “phrase polluted hard negative example generation” You need password to access to the content, go to Slack *#phdsukai to find more. ...