1/ 🚨 Our latest research work, soon to be presented at @wassa_ws during #ACL2023NLP#NLProc, reveals surprising insights about #GPT3’s ability to estimate the big 5 personality traits. Here are some intriguing findings:
@stonybrooku and collaborators have an exciting lineup of papers in the @aclmeeting this year. Also a largish contingent of our students are attending. Check out their talks and posters.
Unfortunately I will taste fomo this year having just moved to Korea.
Current models are good at recognizing textual entailment (RTE). But if an RTE model has a sufficiently high capacity for reliable, robust inference necessary for NLU, then the model's predictions should be consistent across paraphrased examples. #NLProc (1/6)
Heading to Toronto today to attend @aclmeeting. Going to be presenting our work tomorrow morning during the first poster session! Do drop by to learn more about our work! #NLProc#ACL2023
Current models are good at recognizing textual entailment (RTE). But if an RTE model has a sufficiently high capacity for reliable, robust inference necessary for NLU, then the model's predictions should be consistent across paraphrased examples. #NLProc (1/6)
Current models are good at recognizing textual entailment (RTE). But if an RTE model has a sufficiently high capacity for reliable, robust inference necessary for NLU, then the model's predictions should be consistent across paraphrased examples. #NLProc (1/6)
Current models are good at recognizing textual entailment (RTE). But if an RTE model has a sufficiently high capacity for reliable, robust inference necessary for NLU, then the model's predictions should be consistent across paraphrased examples. #NLProc (1/6)