1 code implementation • 11 Oct 2023 • Shreya Havaldar, Matthew Pressimone, Eric Wong, Lyle Ungar
Understanding how styles differ across languages is advantageous for training both humans and computers to generate culturally appropriate text.
1 code implementation • 3 Jul 2023 • Shreya Havaldar, Sunny Rai, Bhumika Singhal, Langchen Liu, Sharath Chandra Guntuku, Lyle Ungar
Emotions are experienced and expressed differently across the world.
no code implementations • 1 Jun 2023 • Shreya Havaldar, Adam Stein, Eric Wong, Lyle Ungar
Meaningfully comparing language models is challenging with current explanation methods.
no code implementations • 24 May 2023 • Salvatore Giorgi, Shreya Havaldar, Farhan Ahmed, Zuhaib Akhtar, Shalaka Vaidya, Gary Pan, Lyle H. Ungar, H. Andrew Schwartz, Joao Sedoc
We present metrics for evaluating dialog systems through a psychologically-grounded "human" lens in which conversational agents express a diversity of both states (e. g., emotion) and traits (e. g., personality), just as people do.
1 code implementation • 31 Jan 2023 • Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch
While Chain-of-Thought (CoT) prompting boosts Language Models' (LM) performance on a gamut of complex reasoning tasks, the generated reasoning chain does not necessarily reflect how the model arrives at the answer (aka.